If you prefer, see it on Slideshare.

1. Unvocalized panting occurs in response to surprise. This panting is part of a generalized increase in physiological arousal. Like the gaping mouth of the “surprised” face, panting prepares the animal for action.
2. For highly social animals (like humans and great apes) the biggest dangers come from other members of our species (conspecifics).
3. Threats from other conspecifics also evoke unvocalized panting. The threatening animal recognizes the panting as a successful provoking of a momentary state of fear in the threatened animal. The evoked fear means that the threatened animal has been successfully cowed. Panting becomes a signal of social deference. As an aside here, we might note that dogs exhibit “social panting” where submissive animals begin panting when a dominant animal (sometimes a human owner) appears.
4. Being able to evoke panting in another animal reassures the dominant animal of its dominant status. Similarly, panting in the presence of another animal serves to communicate one’s submissiveness. For the submissive animal, this communication is valuable because it establishes the animal’s submissive status without having to engage in fighting.
5. In order to enhance the communication of deference, panting becomes vocalized — that is, the vocal cords are activated. Vocalized panting becomes a specific signal of deference or submissiveness.
6. Vocalized panting generalizes to most surprising circumstances.
7. In some primates, “panting-laughter” is reserved specifically for surprise linked to nondangerous outcomes. In highly socialized animals, most dangers are social in origin, so panting-laughter is commonly associated with social interaction.
8. In hominids, panting-laughter becomes explicitly social. Mutual panting-laughter within a group becomes an important signal of reciprocal alliance, social cohesion, and peaceful social relations.
9. The contrast between negative reaction feelings and neutral/positive appraisal feelings evokes an especially pleasant state. Human culture expands on these agreeable feelings through the advent of “humor” as an intentional activity meant simply to evoke laughter.
10. Laughter becomes commonplace in hominid social interaction. In order to reduce the energy cost of laughter, the inhaling-exhaling form is replaced by the more efficient vocalized exhaling (i.e., modern human laughter).

What do we think? I find this to be a convincing theory.

The backbeat is a ubiquitous, almost defining feature of American popular and vernacular music. Clapping or snapping on the backbeats is generally considered by musicians to be more correct than doing so on the strong beats. However, audiences have a tendency to clap or snap on the wrong beats, to the irritation of the performers.

On October 6th, 1993, the blues musician Taj Mahal gave a solo concert at the Modernes Club in Bremen, Germany. The concert was later released as the album An Evening of Acoustic Music. On the recording, Taj Mahal begins to play “Blues With A Feeling,” and the audience enthusiastically claps along. However, they do so on beats one and three, not two and four like they are supposed to. Taj immediately stops playing and says, “Wait, wait, wait. Wait wait. This is schvartze [black] music… zwei and fier, one TWO three FOUR, okay?” He resumes the song, and the audience continues to clap on the wrong beats. So he stops again. “No, no, no, no. Everybody’s like, ONE, two, THREE, no no no. Classical music, yes. Mozart, Chopin, okay? Tchaikovsky, right? Vladimir Horowitz. ONE two THREE. But schvartze music, one TWO three FOUR, okay?” He starts yet again, and finally the audience claps along correctly. To reinforce their rhythm, Taj Mahal continues to count “one TWO three FOUR” at various points during the song.

Every musician working in American popular or vernacular styles has had a similar experience. How do we make sense of such events? To what degree do audiences know that they are supposed to clap on the backbeat in the blues and music like it? Does musical training or practice correlate with knowledge of the backbeat clapping convention? Before answering these questions, we must address the following:

1. Human rhythm perception generally.
2. Syncopation, its musical function and the ability of untrained musicians to parse it.
3. The history of the backbeat in American music.

Background on Rhythm Perception and Production

Musical and rhythmic behavior in humans arose in order to create “a temporal framework, collective emotionality, a feeling of shared experience, and cohesiveness to group activities and ritualistic ceremonies.” (Bispham 2006) Music is a means of establishing behavioral coherency in human groups. We see a shadow of music’s ancestral purpose when an audience claps in unison at a concert.

Group clapping helps unify the audience’s perception of the tactus (also known as the pulse.) This is necessary because tactus choices are ambiguous between individuals, and for individuals across different parts of a piece of music. While the tactus may be subjective, there are some common strategies we use to identify it. There is a “subdivision benefit” in tactus perception, since beats in the slower layer are also present in the faster layer, creating mutual reinforcement. Trained musicians are more likely to map the tactus to a subdivided pulse. Untrained listeners search for the tactus in surface features of the music, but if they do not detect a consistent pulse there, they will seek it at the next metrical level up (Martens 2011).

The variability in tactus perception may have its roots in the nature of the movements we make with our bodies in response to music. Bodily movement does not merely accompany listening; it enhances our ability to listen. We move different body parts with different periodicities—twice as fast with our arms as with our upper torsos, for example. Binary beat structures may arise from the fact that our massive torsos have two maxima and two minima in each periodic cycle of movement. A two-beat period in torso movement corresponds to a four-beat period of movement generally (Toiviainen, Luck & Thompson 2010). Grahn and Brett (2007) identify “[a] bilateral network of motor areas” that mediate both perception and production of rhythm. However, the motor cortex is likely used more for predictable or overlearned stimuli; for novel or unpredictable rhythms, the attentional system is required as well. It is probable that the motor cortex identifies all short-duration rhythmic events, and that the cortex assembles these into holistic structures. Our attention and memory are assisted in this binding process by regular accent structures in the stimuli.

How do we determine which beats in a pattern are accented? We perceive accents in rhythmic patterns even when all of the events have the same volume. We evidently draw on temporal cues to do so. For example, we perceive events as accented when they are not closely followed by other onsets in time (Grahn & Brett 2007).

Phillips-Silver, Aktipis and Bryant (2010) explore the ways that beat entrainment enables us to coordinate rhythmic movements with one another, and the purposes of such behavior. We are able to synchronize to an isochronous pulse even if it is embedded within complex, syncopated and ambiguous rhythms. Entrainment is “an active, self-sustained, periodic oscillation at multiple time scales, enabling the listener to use predictive timing to maintain a stable multiperiodicity pattern and synchronize movements at the tactus or other metrical levels.” We use coordinated rhythmic movements both for literal physical mirroring, and for metaphorical mirroring, i.e. empathy. We require a social context to perform rhythmic entrainment optimally.
Why should we care when anyone else claps during a concert? Perhaps it is because we experience physical rhythmic entrainment as empathy. Musicians like Taj Mahal find it distressing when their audience is not entrained because it feels a failure to emotionally connect.

Syncopation and Rhythmic Tension

Temperley (2010) draws an analogy between harmonic and rhythmic processes in common-practice classical music. Rhythms are organized hierarchically, with notes on weak beats conditional on the adjacent strong beat notes. He proposes a definition of syncopation as a rhythmic event that is improbable by the norms of classical common-practice rhythm. Furthermore, “[s]yncopation represents the aspect of rhythmic complexity that does not relate to repetitiveness.” By this measure, current popular music is extraordinarily rhythmically complex, even though it may be simple harmonically and structurally (Temperley 1999).

Why do we not swiftly become bored with repetitive grooves? Rather than hearing each iteration as another instance of mechanical reproduction, perhaps we experience repetition as a process, with each trip through the pattern opening the possibility of continued repetition or a break in the pattern. A groove is a present that is “continually being created anew.” We give particularity to each repetition based on our memory of the immediate past and our expectations for the future. Participatory discrepancies add power and interest to the groove, as they support the anacrustic tendencies of each iteration (Butterfield 2010). This can explain why a sampled breakbeat can carry more excitement than a recording of a drummer playing a repeated groove. There is a tension between the identical repetitions and the nuances of participatory discrepancy within each repetition, grabbing our attention anew each time they pass by.

Syncopation is intrinsic to African-influenced American musical forms like rock and jazz. While classical music generally aligns stressed syllables in lyrics and important melodic notes with strong beats, rock and jazz routinely place these events on weak beats. Unstressed syllables in rock lyrics, like those of the Beatles, are commonly metrically stronger than adjacent stressed ones. Rock, like jazz, derives its energy from such metrical tension. Rock is predicated on rhythmic counterpoint rather than melodic counterpoint (ibid).

The backbeat is an exceptionally prevalent form of syncopation. It is used to create rhythmic tension and anticipation, eliciting more active and participatory listening. Jazz drumming typically combines backbeats played on the hi-hat with a swung pattern on the ride cymbal. This combination creates a continual sense of anacrusis. The specific beat-upbeat ratio of the swung eighth notes can vary between musicians, and even within a single musician’s phrasing. The continual flow of information provided by swung eighth notes draws focus to the quarter notes—the shortened upbeat eighth note is perceptually grouped both with its predecessor and the following on-beat, binding the groove together into a strong and unmistakable tactus. Likewise, the backbeat, the rubbery beat-upbeat ratio and various forms of syncopation all combine to draw attention to larger metrical structures. All of this rhythmic tension keeps the listener actively engaged, and encourages audience participation. (Butterfield 2011).

How do we parse syncopated rhythms like the backbeat? Fitch and Rosenfeld (2007) tested listeners’ abilities to perceive and reproduce complex syncopated rhythmic patterns. They found that when we become lost in a difficult rhythm, we tend to reset the phase of our internal pulse sense, “re-hearing” the rhythm as less syncopated. The author occasionally mistakes an accented backbeat for the tactus; it is then challenging to reorient to the correct beat structure. When we hear a syncopated pattern against a steady pulse, we may use one of three strategies to parse it:

1. We can simultaneously process both the syncopated pattern and the original pulse.
2. We can attempt to integrate the two into a single coherent stream, perhaps by mentally shifting syncopated events to strong beats.
3. We may reset our sense of the tactus to follow the syncopated pattern, rather than the original pulse.

Fitch and Rosenfeld found that either of the first two strategies may be used, but that the most complex syncopations require the third strategy of resetting. This is especially true when the syncopated rhythm is stated over an implied pulse. Since it is difficult to attend to multiple streams of input simultaneously, the resetting strategy reduces our attentional load. The pull between different streams of metrical information are the source of structured rhythmic tension and resolution in African, Afro-Caribbean, and Brazilian music, analogous to harmonic tension and resolution in western tonal music.

Ladinig, Honing, Háaden and Winkler (2009) tested whether musically untrained adult listeners form hierarchical representations for a rhythmical sound sequence using varying degrees of attention. They found that their subjects performed syncopated patterns better when the syncopations occurred in metrically stronger positions, indicating that musical training is not required to parse hierarchical metrical structures. “Metric salience” is a value assigned to each sequential event in a rhythmic sound pattern according to its position within the pattern, by “recursively breaking down a musical pattern (with an initially specified length) into subpatterns of equal length.” The more subdivisions it takes to reach a given event, the lower its metrical salience. The downbeat is the most salient position, and it would seem natural to clap on the most salient beat—indeed, this is what many untrained listeners do. However, the Afro-Caribbean core of American popular/vernacular music asks us to accent the less metrically salient backbeat instead.

The confusion between accented downbeats and backbeats is exacerbated by the considerable variation in our perception of tempo. While most listeners have a “preferred tempo” range between 80 and 160 beats per minute, salient tempi are commonly perceived as lying well outside this range. Our perception of meter is also quite variable, and can depart dramatically from the notated meter. McKinney and Moelants (2006) examine tapping studies to see whether preferred tempo and implicit meter is dependent on musical content. They find that while we default to tempo ranges centered on 120 beats per minute, dynamic rhythmic accents within the music can draw our perceptions away from this default. While tactus nearly always falls within the preferred tempo range, the perceived tempo may be any one of several different multiples or divisions of the tactus, depending on the distribution of accented rhythmic events in the music. Tempo is more ambiguous in jazz than in metal or punk, which is unsurprising given the difference in those styles’ rhythmic complexity. Interestingly, variation in tempo perception is not affected by musical training.

History of the Backbeat

Baur (2012) defines a backbeat rhythm as one that places percussive accents on weak beats, typically the second and fourth beats in 4/4 time. The backbeat is most commonly played on the snare drum, but it can be accented by any instrument. Originating in Dixieland jazz, country and gospel, the backbeat is now ubiquitous throughout American and global popular music. While accenting weak beats was a common device in American popular music throughout the first half of the twentieth century, the term “backbeat” did not enter common usage until the advent of rock and roll in the early 1950s—appropriately enough, since the backbeat is a foundational component of rock.

Tamlyn (1998) gives an exhaustive historical overview of the evolution of rock rhythms, specifically the snare backbeat. He argues that the backbeat arose independently from several different sources:

• Early jazz banjo and piano accompaniment patterns
• “Chicago-style” drumming in loud tutti sections, final choruses or instrumental solos, both on the snare and hi-hat or choked cymbal
• New Orleans processional drumming, with roots in Africa and the Caribbean
• Handclaps and tambourine hits in sanctified gospel music
• Staccato guitar and mandolin accompaniment in country music
• Slap bass in both country and jazz

The backbeat initially arose as an emphatic embellishment, and gradually expanded over the first half of the twentieth century to underpin entire songs in a variety of styles.

American popular music grew steadily more syncopated over the course of the twentieth century. Huron and Ommen (2006) randomly selected measures of recordings made before 1940 and analyzed their degree of syncopation, defined in this instance as an onset failing to occur at a higher metrical level than that of the previous onset. In other words, we hear syncopation as the absence of an expected rhythmic event in a strong metrical position. By Huron and Ommen’s definition, syncopation can occur at any metrical level, from sub-beats to hypermeasures. They found a steady increase in the quantity of syncopation over time, with the number of syncopated events increased from an average of 1.2 syncopations per measure in the 1890s to nearly 1.8 syncopations per measure in the 1930s. The authors also cite research showing that we learn to anticipate events through statistical learning during exposure to our culture’s music. Rhythmic events on the weakest beats (the smallest subdivisions) are the least common in European-descended music, and therefore are the most surprising when they occur.

The backbeat is a significant component of the Africanization of American music. Baraka (1963) makes the bold claim that “the only so-called popular music in this country of any real value is of African derivation.” He traces the spread of African musical values into America via the slave trade. The percussion-heavy, improvisationally oriented and shouted/chanted music we hear on every pop radio station is informed powerfully by those vestiges of West African music that survived slavery. Generally speaking, African music is rhythmically complex and harmonically static, a neat inverse of Europe’s harmonically rich but rhythmically unsophisticated art music tradition. American musical history is largely informed by the collision between these two musical cultures.

The standard drum kit combines percussion instruments from several different world cultures: “cymbals from Turkey, tom-toms from Africa, and the snare drum from Europe.” (Greenwald 2002) In both African and African-American music, the varying timbres of the percussion ensemble or drum kit fuse into a single perceptual mass. That said, the sophisticated listener can learn to take cues from specific drum instruments.

The “Funky Drummer” template is a cornerstone of hip-hop and many other American dance styles: a phrase beginning with an eighth-note/eighth-note/quarter-note figure (“boom-boom-cha”) followed by greater variety and syncopation (ibid). While traditionally the bass drum has stated the pulse in dance music, in hip-hop, it does so rarely. Instead, after sounding the first downbeat in each hypermeasure, the bass drum often falls into a sparse syncopated pattern. The snare drum is most often placed on the backbeats, and occasionally on additional weak beats. Stewart (2000) traces this rhythmic style to three major sources: African and Caribbean culture as filtered through New Orleans; a style of gospel singing and clapping known as “rocking and reeling;” and bluegrass and string band music.

Why is understanding of the backbeat so unevenly distributed? America have resisted the backbeat for moralistic reasons that conceal racist and classist attitudes. The backbeat and its associated music styles have been considered throughout their history to be disreputable, low-class, primitive and barbaric, even perceived as threatening the moral fabric of society entirely. This is unsurprising, given the backbeat’s origins in the music of marginalized groups: African-Americans, rural whites and immigrants. Stewart attributes the moral dimension of resistance to the backbeat to funk’s associations with bodily functions and sexual odours—terms of praise among funk musicians include “dirty,” “filthy,” “raw,” “stanky” and “nasty.” These bodily associations are intrinsic to funk’s appeal, particularly its ability to inspire audience participation and dancing. While the funk/hip-hop rhythmic template is extraordinarily compelling to people across the world, many Americans find its Afrocentrism threatening. The jazz drummer Max Roach is quoted by Greenwald as saying that “[t]he thing that frightened people about hip-hop was that they heard rhythm—rhythm for rhythm’s sake.”

As long as Americans devalue the bodily intelligence represented by the backbeat, they will naturally continue to misunderstand it. This is unfortunate. McClary (1989) argues that it requires greater skill and musicality to produce the groove in a dance-oriented Earth, Wind & Fire song than to generate “the self-denying, ‘difficult’ rhythms derived by externally generated means. One need only observe professional classical performers attempting to capture anything approaching ‘swing’ (forget about funk!) to appreciate how truly difficult this apparently immediate music is.” We may hope that backbeat-based dance music will continue to find the acceptance and understanding that has thus far failed to match its popularity.

References

Baraka, A. (1963). Blues People: Negro Music in White America. New York: Quill.

Baur, S. (2012). Backbeat. The Grove Dictionary of American Music, 2nd edition.

Bispham, J. (2006). Rhythm in Music: What is it? Who has it? And Why? Music Perception, 24(2), 125–134.

Butterfield, M. (2011). Why Do Jazz Musicians Swing Their Eighth Notes? Music Theory Spectrum, Vol. 33, No. 1, 3-26.

Butterfield, M. (2010). The Power of Anacrusis: Engendered Feeling in Groove-Based Musics.” Music Theory Online 12 (4).

Fitch, W. T., & Rosenfeld, A. J. (2007). Perception and Production of Syncopated Rhythms. Music Perception, 25(1), 43–58.

Grahn, J. A., & Brett, M. (2007). Rhythm and Beat Perception in Motor Areas of the Brain. Journal of Cognitive Neuroscience, 19(5), 893–906.

Greenwald, J. (2002) Hip-Hop Drumming: The Rhyme May Define, but the Groove Makes You Move. Black Music Research Journal, Vol. 22, No. 2, 259-271.

Huron, D. and Ommen, A. (2006). An Empirical Study of Syncopation in American Popular Music, 1890–1939. Music Theory Spectrum, Vol. 28, No. 2, 211-231.

Ladinig, O., Honing, H., Háaden, G. and Winkler, I. (2009). Probing Attentive and Preattentive Emergent Meter in Adult Listeners Without Extensive Music Training. Music Perception 26. 4 (Apr): 377-386.

Martens, P. (2011). The Ambiguous Tactus: Tempo, Subdivision Benefit, and Three Listener Strategiex. Music Perception 28. 5 (Jun 2011): 433-448.

McClary, S. (1989). Terminal Prestige: The Case of Avant-Garde Music Composition. Cultural Critique, No. 12, pp. 57-81.

McKinney, M. F., & Moelants, D. (2006). Ambiguity in Tempo Perception: What Draws Listeners to Different Metrical Levels? Music Perception, 24(2), 155–166.

Phillips-Silver, J., Aktipis, C. A., & A Bryant, G. (2010). The Ecology of Entrainment: Foundations of Coordinated Rhythmic Movement. Music Perception, 28(1), 3–14.

Stewart, A. (2000). ‘Funky Drummer’: New Orleans, James Brown and the Rhythmic Transformation of American Popular Music. Popular Music, Vol. 19, No. 3, 293-318.

Tamlyn, G. (1998). The Big Beat: Origins and Development of Snare Backbeat and other Accompanimental Rhythms in Rock ’n’ Roll. PhD thesis, University of Liverpool.

Temperley, D. (2010). Modeling Common-Practice Rhythm. Music Perception: An Interdisciplinary Journal, Vol. 27, No. 5, pp. 355-376.

Temperley, D. (1999). Syncopation in Rock: a Perceptual Perspective. Popular Music, Volume 18/1.

Toiviainen, P.; Luck, G., & Thompson, M. (2010). Embodied Meter: Hierarchical Eigenmodes in Music-Induced Movement. Music Perception 28. 1: 59-70.

Title

The Drum Loop: a Self-Guided Tutorial System for Programming Dance Rhythms

Introduction

Dance music production software has never been more accessible. However, even “beginner-oriented” programs like Apple’s Garageband presume significant musical knowledge. Would-be dance producers who have access to formal music education are ill served by Eurocentric teaching methods and curricula. By and large, those wishing to learn drum programming are largely left to their own devices. This is unfortunate, because learning how to create beats does not only benefit electronic dance musicians. The ability to actively create and alter rhythms and to match their visual notation with the resulting sounds in real time sharpens the rhythmic abilities of any musician.

Most dance musicians must self-teach, and they face some significant obstacles in doing so. Nearly all music production tools are based on the keyboard/piano roll or multitrack tape/DAW paradigms. Beginners struggle to learn these visualization schemes on top of the musical concepts underlying them. A simplified and more intuitive interface would help to prevent frustration and abandonment of musical study. The author believes that a clock face metaphor is a more intuitive visualization scheme for the loops that form the basis of dance music drums. The present project consists of the design of a radial drum machine interface and a series of rhythm programming exercises. User evaluations of the program’s usability and effectiveness will inform the final design.

Motivation

Conventional music education focuses primarily on melody and harmony, and tends to neglect rhythm outside of the melodic context. Students of dance music must piece together guidance as best they can from percussion study resources, ad-hoc peer-to-peer learning and trial and error. A systematic and self-guided dance rhythm programming tool would fill this vacuum neatly.

Why take the study of dance music seriously? Music teaching should operate “from within authentic music making contexts.” (Martin 2012) Dance music is accessible enough that even beginners can produce it, thus “folding musical analysis into musical experience.” (Marshall 2010) Drum programming should be part of an overall widening of the curriculum to include non-western and non-classical music. Decanonization is a worthwhile goal for two reasons: 1) students will remain more engaged when studying music they know and like, and 2) dance music is worthy of serious study in its own right. Digital production tools are not merely musical instruments; they carry with them an entire philosophy of music-making. The digital studio collapses composition, recording and editing into a single act, and expands the definition of the word “musician” beyond traditional performers and composers to include anyone with the patience and the will to learn the software and explore its possibilities (Thibeault 2011).

Music visualization can significantly aid aural understanding. Visual reinforcement of the aural experience creates a dynamic multisensory feedback system, which improves the learning and retention of rhythmic patterns (Jylhä, Ekman, Erkut & Tahiroğlu 2011). The best visualization methods take advantage of existing image schemas widely used to conceptualize music. These schemas include such bodily metaphors as containers, cycles, and the notion of center-periphery. Software interfaces and visualizations using body-centric image schemas will be easier to learn and remember (Wilkie, Holland, & Mulholland 2010).

Drum programming interfaces generally follow either the standard MIDI piano roll format or the time-unit box system. There is some precedent for a radial “clock face” model for music loops. The turntable is one of the most immediate, and it persists in DJ software like Serato. Other clockface representations of repetitive music include Joy Mountford’s Soundscapes instruments (Levin 2000) and the circular representations of performance data and music theory cited by Benadon (2007). That said, very little software exists that combines a radial loop visualization with an accessible time-unit box system.

Beginner-oriented software must place simplicity above all other considerations. Limiting options need not limit creativity. The more sophisticated music production tools can stifle creativity under the weight of option paralysis. A smaller feature set can be easily mastered, allowing users to quickly move on to musical expression (Magnusson 2010). Rich inspiration for beginner-friendly user interface design can be found in music games like Guitar Hero, Dance Dance Revolution and the like. Such “rhythm games” must motivate players through many hours of disciplined practice, without any external instructors. Like all the best learning experiences, successful music games use progressive levels of difficulty and frequent rewards for success and persistence to produce a pleasurable feeling of flow. While the games do not enable much creative music-making, they have a well-documented ability to teach players how to listen actively and to think more like musicians (Gower & McDowall 2012).

Rhythm games have one major limitation as music-making tools: self-expression is fundamentally incompatible with an unambiguous win condition. It seems more promising to create music tools with game-like interfaces, rather than music games per se (Rosenstock 2010). Software will never be able to be a satisfactory judge of musical quality; users and/or their teachers must decide whether their musical ideas are satisfactory or not.

Goals

The present project aims to create a program that teaches beginner musicians how to program dance beats, and to evaluate this program’s effectiveness. Through a series of interactive exercises that gradually build in complexity, users will gain a hands-on understanding of rock, pop, hip-hop and techno rhythms. Upon completion of the drum programming exercises, users will be better equipped both for study of traditional instruments and for more sophisticated sequencing software like Garageband, Logic or Ableton Live.

The user interface will use a radial time-unit box system rather than the more conventional linear “ice cube tray” model. The radial arrangement makes the symmetries and asymmetries of particular beats significantly more apparent to the eye. Stronger beats fall on the cardinal points, with weaker beats falling at “odd” angles. Syncopated patterns can be identified and understood easily by their differing symmetries from the main groove.

Exercises will take the form of generic hip-hop, rock, techno and Afro-Cuban rhythms, which the user may customize within constraints. The first programming exercises will constrain the user significantly. A drum pattern will be provided, with all parts locked down except for one instrument, likely a cowbell or shaker. The user will be free to place hits on this instrument where they like, with a guarantee that any location in the pattern will have a musical-sounding result. Users advance when they are satisfied with their drum pattern. In each subsequent exercise, more instruments within the drum patterns are unlocked. The user becomes able to move the hi-hats, then the kick and snare. All patterns will have a locked kick drum on the first downbeat, along with a locked snare or handclap on the first backbeat. This guarantees that all drum patterns will sound basically musical, keeping the user in a state of pleasurable flow. At any time, users may switch to “free programming mode,” in which they can place drum hits anywhere. Patterns can be saved and exported as audio files.

Two user studies will be conducted, evaluating the program’s effectiveness in conveying musical knowledge and doing so in a pleasurable, flow-inducing way. The studies will primarily focus on beginners, but will include some musicians with diverse training backgrounds as well. The results of the first study will be used to refine the user interface and exercises. The second study will test the hypothesis that the radial presentation and progressive relaxation of constraints enhance users’ learning and retention of rhythmic concepts.

Work Plan

The project will consist of five main phases:

1. Design of the radial drum machine in Max/MSP.
2. Creation of the drum programming exercises.
3. Developing and implementing a user testing framework.
4. Revising the drum machine interfaces and exercises based on the results of user testing.
5. Conducting a second round of user testing, and analyzing the results.

Milestones and Dates:

• January – March 2013: Gather sources, design drum machine
• March 15, 2013: Fully functioning drum machine
• May 1, 2013: Final UI design
• June 1, 2013: Create drum programming exercises
• July 2013: First interaction study
• August – September 2013: Refinement of UI and drum programming exercises
• October 2013: Second interaction study
• November 2013: Collate and analyze study data, complete written portion
• December 2013: Defense

References

Benadon, F. (2007). A Circular Plot for Rhythm Visualization and Analysis. Music Theory Online, Volume 13, Issue 3.

Gower, L. & McDowall, J. (2012). Interactive Music Video Games and Children’s Musical Development. British Journal of Music Education, Volume 29, Issue 1, 91 -­ 105.

Jylhä, A.; Ekman, I.; Erkut, C.; & Tahiroğlu, K. (2011). Design and Evaluation of Human–Computer Rhythmic Interaction in a Tutoring System. Computer Music Journal, Volume 35, Issue 2, 36 – 48.

Levin, G. (2000). Painterly Interfaces for Audiovisual Performance. MS Thesis, Massachusetts Institute of Technology.

Magnusson, T. (2010). Designing Constraints: Composing and Performing with Digital Musical Systems. Computer Music Journal, Volume 34, Number 4, pp 62 – 73.

Marshall, W. (2010). Mashup Poetics as Pedagogical Practice. In Biamonte, N., ed. Pop-Culture Pedagogy in the Music Classroom: Teaching Tools from American Idol to YouTube. Lanham, MD: Scarecrow Press.

Martin, J. (2012). Toward Authentic Electronic Music In The Curriculum: Connecting Teaching To Current Compositional Practices. International Journal of Music Education 30: 120.

Rosenstock, J. (2010). Free Play Meets Gameplay: iGotBand, a Video Game for Improvisers. Leonardo Music Journal, Vol. 20, 11–15.

Thibeault, M. (2011). Wisdom for Music Education from the Recording Studio. General Music Today, 20 October 2011.

Wilkie, K.; Holland, S.; & Mulholland, P. (2010). What Can the Language of Musicians Tell Us about Music Interaction Design?” Computer Music Journal, Vol. 34, No. 4, 34-48.

The major musical event of the past hundred years (in western cultures anyway) has been the hybridization between European linearity and African (and Latin American and Asian) circularity. This has been most dramatic in the United States, with its enormous populations of immigrants and descendants of slaves. Our popular music has been getting more and more circular (more “African”) with every passing decade, from jazz to R&B to rock to funk to hip-hop. And our popular music makes its presence felt in every corner of the world.

James Brown is a critical figure in this story because he did his best work at a time when black Americans were beginning to assert pride in their roots and ethnic identity. (“Say it loud, I’m black and I’m proud!”) JB made it an explicit goal to push his music into a more African direction: complex rhythmic grooves, minimal harmonic activity, improvisational chants instead of sung melodies, trance-like repetition over long time scales. “Sex Machine” isn’t even his most repetitive groove. Check out “There Was A Time,” a four-bar cell repeated more or less identically for over seven minutes.

And by the way, JB’s love of Africa was reciprocated; he influenced a generation of African musicians, most famously Fela Kuti.

So, to finally answer your question. If you approach “Sex Machine” with a western classical value system, it certainly is going to seem “monotonous.” The classical term for that guitar riff is an ostinato, from the Italian word for “obstinate.” Hardly a term of endearment. You may well enjoy the song, but you’d naturally imagine that it’s intellectually unsatisfying and therefore boring to play.

Coming at “Sex Machine” from an Afrocentric perspective is quite different. The groove is so devastating, so effortless, so transporting. Adding variations to make it more narrative or “interesting” would only water it down and diminish its power. The groove isn’t really aimed at your prefrontal cortex. It’s aimed at the rest of your brain, your limbic system and motor cortex, not to mention your entire self from the neck down. The point of funk is to dissolve your conscious self into the holistic unity of the groove. As JB says in “Give It Up Or Turnit A-loose,” “Check out your mind, swing on the vine, in the jungle brother.” And as Prince sings, “There’s joy in repetition, there’s joy in repetition, there’s joy in repetition, there’s joy in repetition.”

Playing a James Brown groove is much harder than it seems. Learning the riff is easy enough, but sustaining it at length takes Jedi-like focus. Playing funk well demands a certain relaxed intensity, and if that sounds like an inherent contradiction, it is. Sustaining the balance between looseness and discipline takes more than musical skill; it requires you to be able to suspend your anxieties, your distracting thoughts and your self-consciousness. Fortunately, the groove itself is a great tool to help you do exactly that.

This paper will explore the problem of how software can best be designed to help novice musicians access their own musical imagination with a minimum of frustration. I will examine a variety of design paradigms and case studies. I will hope to discover software interface designs that present music in a visually intuitive way, that are discoverable, and that promote flow.

Interaction Design Principles

Any user interface, musical or otherwise, must operate within the limits of our ability to draw metaphorical connections between visual images and abstract concepts. A software interface is not a neutral intermediary between the user and the work. It guides and shapes the final product, especially when the user is inexperienced. Software interfaces do a great deal of implicit teaching, and indeed may be the only instructor that some musicians ever encounter. A given interface’s constraints can be obstacles to creativity, but sometimes constraints can be drivers of creativity in their own right.

Visualizing Music

Computer-based music production involves the eyes as much as the ears. The representations in audio editors like Pro Tools and Ableton Live are purely informational, waveforms and grids and linear graphs. Some visualization systems are purely decorative, like the psychedelic semi-random graphics produced by iTunes. Any investigation into digital music pedagogy must begin with an examination of music visualization systems.

Notation is the oldest (known) method of visualizing music. Western notation is a very neat and compact system, unambiguous and digital. It can be effortlessly converted to and from MIDI data. But western notation has some limitations, especially for contemporary music. The key signature system works well for diatonic major and minor keys, but is less helpful for modal music and is fairly worthless for the blues. After one hundred years of jazz, there is no good way to notate swing other than to write the word “swing” at the top of the score. The further an instrument departs from the piano, the more difficult it is to map it to a notation system. How would one notate the music of Eric B and Rakim, or Aphex Twin, or Girl Talk?

The MIDI “piano roll” has a mostly straightforward one-to-one mapping to western notation. MIDI therefore has some of the limitations mentioned above. However, it offers several advantages. The piano roll shows not only which notes are being played and when, but exactly how long they’re held. Note velocity is indicated via color or vertical lines. Pitch bend data can convey microtonal nuance. Rhythmic nuance can be conveyed through the precise positioning of events against the grid.

As software becomes more sophisticated in its ability to extract pitch data from audio recordings, we can begin to manipulate the audio with the same ease as MIDI. The pitch-correction program Melodyne enables MIDI-style editing of polyphonic audio recordings, both in piano roll view and in traditional notation. The actual pitch contour is shown as a series of lines, and the abstracted “score” is a corresponding series of orange waveform blobs. The blobs’ thickness shows dynamics.

Notation conventionally shows time moving from left to right. But this is not necessarily the most intuitive way to visualize time. Rhythm games like Dance Dance Revolution and Guitar Hero show time as a track projecting into the screen, along which the player moves forward, as if on a train. The pioneering game FreQuency shows the song as a polyhedral tube, with each face of the tube standing for a different instrumental track.

Which visualization scheme is the best? To answer that, we must examine the nature of metaphors and how we make sense of them.

Bodily Image Schemas in Music

In their book Metaphors We Live By, George Lakoff and Mark Johnson observe that we frame metaphors in terms of states of our bodies. Indeed, body states are the only basis for abstract thought that we possess. The closer a metaphor is to a state of the body, the easier it is for us to understand. Metaphors that are several layers of abstraction removed from bodily states will be difficult to learn and remember. A good software interface must hew closely to our need for body metaphors cognition.

Music has a broad set of commonly used bodily metaphors. The most basic bodily experiences we relate to music are rhythm and repetition. We experience these phenomena throughout our inner experience, from our heartbeats and respiration to our gait. We also use a variety of spatial metaphors for music, referred to by Wilkie et al as image schemas. Such musical image schemas include containers, cycles, verticality, balance, the notion of center-periphery, and (in the case of western melodies) a narrative of source-path-goal.

When we conceive melodies, we think of the line moving over a metaphorical landscape, with altitude standing in for pitch. We might say, “The melody starts on F, goes up to Bb, down to A, and then lands back on F.” The pitch-as-height metaphor is muddied by the circularity of pitch class, and by the fact that we feel ascending pitch movement differently from ascending. We may use alternative image schemas; it is common to visualize higher pitches as brighter, and lower pitches as darker.

We are on more consistent metaphorical footing with the notion of the tonic as “home base.” We imagine a piece that modulates through different keys as going out on a journey and then returning home. Both a piece of music and a physical journey are events ordered in time, so the metaphorical connection here is effortless.

Our metaphors acquire an additional layer of abstraction when we conceive of music not as a sequence of events, but a nested collection of objects. When we say that a piece of music is in the key of F minor, we imagine F minor as a container from which the music draws notes, like Legos from a box. We think of chords as vertical stacks of notes, again evoking Legos.

We approach software equipped with our familiar bodily image schemas, learned and innate. The highest praise we can give to an interface is that it is “intuitive,” meaning that we can apply prior knowledge and familiar image schemata: innate, sensory-motor, embodied, cultural, or expert. Wilkie et al have gathered a comprehensive list of familiar bodily metaphors for music. These include:

• A piece of music is an object.
• A whole piece of music is constructed from a number of parts.
• Harmonic and melodic progression is movement along a path from a source to a goal.
• Musical repetition is a pattern.
• Keys and chords are containers for notes.
• Unexpected musical change is a diversion, a change in spatial direction.
• High pitch is up; low pitch is down.
• Intervals have sizes or lengths.
• A rest or silence is an object.
• Musical silence is a blockage to motion.
• Key/chords are related to the tonic in the familial sense.

An interface that employs these metaphors will be easier to learn, and an interface that does not will resist learning. For example, on the piano keyboard, pitches are arranged left-right rather than high-low. I have played basic piano for twenty years and still have difficulty immediately recalling whether the higher pitches are on the right or left. Similarly, beginning guitarists struggle with the fact that the lower-pitched strings are physically located above the higher ones. Software designers, unconstrained by ergonomic considerations, can and should hew closer to intuition.

Tool as Participant

Music has always been shaped in part by the tools used to make it. Music written for piano will be more concerned with dynamics than music for harpsichord. The active role played by tools has never been more critical than in the digital realm. The presets and defaults in a popular piece of software will leave indelible stamps on the music they produce. When Propellerheads’ Reason attained widespread popularity a few years ago, its default drum loops became ubiquitous in television commercials. The most dedicated musicians will find ways to produce the sounds in their heads regardless of the tools. But most musicians are not that dedicated, especially the beginners. For the casual musician, a tool’s affordances will have a strong impact on their work.

Electronic musicians tend to begin their work by playfully experimenting with a piece of equipment or software, a period of open-ended “knob-twiddling.” The discoveries made during this period, particularly those not intended by the musician or the software’s designers, are crucial raw materials for the more formal composition and editing that follows. One subject interviewed by Gelineck and Serafin described his tools as “having a life of their own.” In general, there is a feeling that the electronic musician’s tools are active, even intelligent participants.

A central attraction of packages like Logic or Ableton Live is their large libraries of music samples, instruments and effects presets. These prefabricated building blocks give qualms to some music educators. Why learn “creativity” when the student can simply throw loops together from a folder and call it a day? If a track is primarily built from presets, can its creator really be said to have created anything? Should the creators of the presets be considered the “real” composers?

The question of electronic music authorship becomes even more vexed when the software generates ideas ex nihilo. Many MIDI sequencers offer the ability to generate notes semi-randomly within particular scales or chords. Ableton Live has an effect called Beat Repeat that semi-randomly shuffles pieces of audio, sometimes with startlingly musical results. Beat Repeat’s output can be strongly reminiscent of classical embellishments or jazz improvisation. If I apply Beat Repeat in a track, should I consider the computer a co-composer? Or the programmers who created Beat Repeat?

Music software steers its user toward the sounds that can be produced most expediently. The availability of features and the ease with which they can be learned and accessed convey implicit lessons to the inexperienced user. In this sense, all music software is educational. What lessons does it teach? Are they the right ones? Will the software-as-teacher guide and inspire students or stultify and limit them?

Constraints

Audio programming environments like SuperCollider and Max/MSP offer the skilled musician virtually unlimited sonic freedom. Rather than liberating creativity, however, these tools can just as easily stifle it under the weight of option paralysis. Music made with such tools frequently never makes it past the experimentation stage into fully-realized works. Performances can all too easily take the form of technical demos.

Simple, limited interfaces have two major virtues. A small feature set can be learned quickly, and its most obvious uses will quickly become tiresome. Magnusson speaks approvingly of interfaces that “proscribe complexity in favor of a clear, explicit space of gestural trajectories and musical scope.” If presented with a finite feature set, users are encouraged to move quickly past the knob-twiddling stage and into finding musically expressive uses for the tool.

How do interface designers balance the need for complexity and surprise with the need for constraint and simplicity? The following section addresses a variety of approaches to meeting this challenge.

Pedagogical Strategies For Music Technology

Beginner musicians face a frustrating situation. They can hear the desired sounds in their heads, but it is many months or years before they can produce those sounds with their instruments. Many would-be musicians are unable or unwilling to persist through the tedium of rote practice to reach the stage where expression and pleasure begin. The computer has a lower barrier to entry than most acoustic instruments. Producing music that sounds good is practically effortless. For that reason, software can be an invaluable motivator, bridging the gap between conception and execution. Rather than supplanting traditional musicianship, software can motivate beginners who would otherwise give up in the early stages of learning.

Computers have primarily been in music education as a more convenient delivery system for traditional pedagogy: reading materials, drills, and multimedia storage and playback. Treating the computer as a valid expressive tool in its own right, worthy of a central role in the curriculum, will take some adjustment among educators. The computer is fundamentally unlike other music-making tools — producing flawlessly executed performances and infinite loops is effortless, while expressiveness, improvisation and idiosyncrasy are challenging. The following sections list some sources of inspiration for successful use of software for music education.

Learning from Repetition

Western classical tradition takes the linear narrative as its defining metaphor. Electronic dance and pop music are based on a very different basic image: the endless loop. Copy and paste is the defining gesture of digital editing tools, and infinitely looping playback their signature sound.

The cyclic nature of pop, dance and hip-hop music are obvious (and much lamented by “sophisticated” musicians.) Upon examination, however, this loop-centric bias appears throughout contemporary art music as well, with African-American dance music as the fundamental cultural transmission vector. Susan McClary observes:

The proliferation of [cyclic repetition] across genres has not been noticed very much, in large part because they do not share the same audiences. The devoted fans of Goldie or Missy “Misdemeanor” Elliot don’t usually attend Steve Reich concerts, nor do many of the symphony subscribers who admire the works of John Adams involve themselves in the dance-club scene or participate in raves… Yet the genres often sound astonishingly similar, especially in their ways of structuring time… Given its ubiquity, black pop music would seem to be the element most clearly responsible for converting our collective sense of time from tortured heroic narratives to cycles of kinetic pleasure. As Prince sings, “There’s joy in repetition!”

Software is ideally suited to producing endlessly repeated loops. Creating a two-bar loop using a computer is significantly easier than building a long, linear, narratively structured melody. This fact is of great benefit to the music educator, because the loop is an excellent teaching tool. There is no better way to deeply internalize a musical concept than to hear it repeated on a loop several hundred times.

Repetition is fundamental to all forms of human learning. Neuroscientists use the word “rehearsal” to describe the mental repetition of information as we transfer it from short-term into long-term memory, where repeated firings of certain networks of neurons strengthen their connections until a persistent pattern is firmly wired in place. The connection between this sense of rehearsal and the musical sense is not at all coincidental.

Loops can, of course, be any length. A loop might encompass a few notes, a few measures, a few phrases or an entire piece. The key to effective music learning is “chunking,” breaking a long piece into short, tractable segments and then building those segments into larger meta-segments. The length of looped chunks can be customized based the level of the students — beginners will work with looped single measures or phrases, while more advanced students can loop through passages and sections. Chunking helps get students to musical-sounding results quickly. Rather than struggling painfully and haltingly through a long passage, students can attain mastery over a shorter one, which builds confidence. Furthermore, chunking can help make feedback more immediate and thus more effective.

Saville cites the music educator’s truism that “accurate feedback may be the single greatest variable for improving learning.” The longer the delay between the performance and the feedback, the less effective it is. It is best to give feedback in the moment, while the student plays along with the loop, “in the heat of battle.” The loop can continue to run indefinitely, so students need not lose the flow when they drop a note or receive feedback.

Dance music tools like Ableton Live make it easy to isolate sections of recordings, loop them, and alter their tempo or key independently. Melodies can also be entered via MIDI, though these will not have the organic feel of a recording of real musicians. Still, MIDI has the advantage of nearly infinite flexibility. Also, any public domain work can be found in MIDI format on the internet with a simple Google search. MIDI is also highly amenable to copy-and-paste methods of composition. In their study of teachers’ use of music technology in the classroom, Stuart Wise, Janinka Greenwood and Niki Davis describe a class that used Sibelius to teach western notation. Students quickly discovered its potential as a MIDI sequencer, rather than just a way to prepare scores for eventual human performance. One young student created a series of complex arpeggios by means of simple copying and pasting, a compositional idea that almost certainly would not have come to fruition via pencil on paper.

In an ideal world, the loop would completely replace the metronome for music practice. The deadening tick-tock of the metronome demoralizes students, and is difficult to relate to a lively beat. Practicing over an actual nuanced groove offers a vastly richer and more engaging practice experience. Furthermore, simply listening to the loop itself can create a gratifyingly trancelike, meditative feeling, as fans of repetitive electronic dance music will attest. This meditative state is highly conducive to flow, and it can turn repetitive drilling into a pleasurable act.

Learning from the Studio

Outside of the classical world, the canonical version of a piece of music is a recording rather than a score or performance. The interpretation on a well-known recording can become coextensive with the work itself. This is especially true in improvised forms like jazz, and in aural traditions like country and blues. In the current musical culture, we experience live music through the lens of intense familiarity with the canonical recordings. Given the primacy of the recording, it is an uphill battle to get music students to engage emotionally with notes on a page. The score becomes much more tractable and approachable after a close study of a recording. As described above, the ability to effortlessly loop a recorded passage in any key at any tempo supplements the score with much-needed aural context. Scores cannot represent timbres, sonic effects or performative nuance the way recordings do. Students of jazz or country or blues will not have much in the way of scores to begin with, making the digital manipulation of recordings that much more valuable.

Thus far, we have considered only recordings of live performances. But recordings need not be a document of a contiguous series of physical events. Tape editing made it commonplace to spice together ideal performances from many takes. Audio editing tools make such splicing trivially easy. More significantly, they also make it possible to build recordings without an actual “performance” ever taking place. The tradition of concert realism that prevailed in the first half of the 20th century has been supplanted by hyperrealism or outright surrealism. We no longer expect a recording to relate back to a group of people in a room playing instruments at the same time. Producers and recordists have become musicians in their own right, often acting as the central or sole creative figures in the making of recordings.

While theorists from Walter Benjamin onwards have lamented the alienation brought about by our recorded music culture, Mark Katz gives us reason to be more sanguine. An individual with a laptop in a bedroom can create fully formed musical works that a few decades ago would have required a small army of musicians and engineers. If I download an mp3 posted by such a bedroom producer on the internet, I have an almost perfectly unmediated view into the artists’ creative intent. Such immediacy and intimacy would have been a rare privilege indeed not so long ago.

As the price of hardware and software plummet, schools are increasingly able to build full-featured digital recording studios. Matthew Thibeault urges music teachers to think of the studio not just as a collection of gear that can be used to document the “real” performance, but as a musical instrument in its own right, carrying with it an entire philosophy of music-making. Educators should recognize that the studio is the locus for most of the musical creativity of the past several decades, and that composition, recording and editing have collapsed into a single act. Even “realistic” performances are usually highly digitally processed. For pop songs, the distinction between songwriting, performance, recording, editing and mixing is blurring to the point of meaninglessness. To meaningfully participate in the musical world, students must become familiar with the studio’s particular demands and affordances.

The skills needed in the studio are quite different from the skills needed on the stage. Digital audio editing diminishes the need for flawless virtuoso performances. It increases the need for creative sequencers and editors, who can work together with performers at any skill level to produce a musical-sounding result. A casually tossed-off improvisation or playful throwing together of sounds can produce better music than hours of sweating over a score. The performer need not even be aware of or involved in the creation of the musical idea; it is common to create a recording using sampled and otherwise decontextualized performances. Such recordings can be more affecting than if the performer had deliberately delivered the finished product.

Thibeault describes his own exposure to the studio as instrument:

I have now recorded myself harmonizing with my voice, recorded multiple takes on different instruments to overlap them, as Stevie Wonder did with his classic albums of the 1970s. For music educators who wish to create a recording studio, it’s worth remembering that the studio can create these pathways, taking students down roads that concerts never can. As students learn to use the studio as an instrument, it’s also possible for them to dream in new ways, imagining music that they would not be able to imagine without these different pathways in.

The studio expands the definition of the word “musician” beyond traditional performers and composers to include anyone with the patience and the will to learn the software and explore its possibilities. Brian Eno, one of the most prominent and influential musicians in the world, is at best a rudimentary instrumentalist and singer; he earned his place in the history of music with his virtuoso “playing the studio.”

Music education should be serving would-be Brian Enos, not just would-be Yo-Yo Mas and Wynton Marsalises. There are emotional aspects to studio work that are just as important for students to learn as the technical aspects. Live music demands flawless, error-free performance. The studio is highly tolerant of mistakes, and unintended sounds are frequently the most valuable. The studio releases musicians from the anxiety of an audience, but creates an entirely different anxiety in the face of the microphone and its clinical surroundings, and the seemingly mysterious workings of the software that is recording the sound. It would be unfair to prepare music students for one situation and not the other.

Learning from Dance Music Producers

Musicians who wish to learn hip-hop, techno and other electronic dance music (EDM) styles are left mostly to their own devices. While software tutorials are widely available, it is difficult to find relevant learning materials about the music itself. The diatonic harmony taught in introductory music theory classes sounds out of place in electronic dance music. The blues, modal and exotic harmonies that are idiomatic to EDM only become available to most music students at advanced levels. EDM producers are left to stumble across their desired chords and scales by trial and error. Dance musicians’ ad hoc learning strategies have nevertheless been proven remarkably effective, honed through decades of practical usage. Rather than trying to supplant such bottom-up learning, formal music instruction should incorporate its best practices.

Some music educators have begun to fill the vacuum. Michael Hewitt’s Music Theory for Computer Musicians is a fairly typical introductory-level theory text, but with an interesting twist: it presumes familiarity with production and sequencing software, and no familiarity with classical notation or terminology. For example, Hewitt explains standard Western notation in terms of the MIDI piano roll. It is fascinating to me to see MIDI treated as the baseline standard, and notation as an alien visualization scheme. As the use of production software spreads, students are likely to enter their first music class with some exposure to MIDI; meeting them on familiar territory will ease their musical growth.

Hewitt takes a similarly forward-looking approach to his text Composition for Computer Musicians. Again, the book presumes familiarity with Logic, Ableton Live, Reason and similar software. He introduces scales and modes that are useful to EDM, presenting the major scale as no more central or important than any of a number of exotic scales. He then presents harmony using the copy-and-paste paradigm comfortable for MIDI users. He begins by duplicating a melodic line and transposing it up a perfect fifth, observing approvingly that parallel fifths are idiomatic to the music of Indonesia. This kind of admirable decanonization extends a welcome mat to those students coming from non-western cultural traditions. Only later does Hewitt introduce full chords and “proper” western voice leading. While this approach would produce dreadful classical music, it gives students of EDM exactly the sounds they are seeking.

Another virtue of Hewitt’s approach is his implicit Afrocentricism. He addresses drum programming early and deeply, covering a variety of rhythmic styles in detail. He also moves quickly from the drum sounds’ placement in the bar to a discussion of shaping their timbre. He recognizes that musical content and sonic content are inseparable, and that timbre is as easily manipulated in software as any other musical parameter. Furthermore, he gives the impression that melody and harmony are decorations of the rhythm. This is a welcome corrective to western classical pedagogy’s neglect of the groove.

The significance of Hewitt’s approach extends far beyond hip-hop and techno producers. His method has promise for music education generally. Computer-literate students will find music production software much easier to learn than music itself, the same way that they find Microsoft Word easier to learn than good writing. Music educators can take advantage of production software to make learning composition and theory more meaningful, interactive and engaging for students working in any style. Software is in many ways a more attractive learning environment than the classroom. Feedback is instantaneous, the musical results of your choices are obvious, and your ears can be the judge of the validity of your ideas. Afrocentricism, multiculturalism and the copy-and-paste aesthetic are similarly valuable to any music student, not just those learning the conventions of EDM.

There is a strong analogy to be made between the role of computers in music education and math education. In both cases, the computer is much better at executing algorithms than people are. The focus of education should shift from executing algorithms to understanding how the computer executes them, and how to express them in computer-readable terms. Hewitt’s germane example is the arpeggiator function included in most sequencers. The computer can effortlessly spin out repetitive symmetrical note patterns; the student needs to understand the meaning and content of those patterns, not how to execute them manually. There is also the strong analogy between composition and computer programming. Both can be clearly visualized using flowcharts. Hewitt makes good use of the flowchart model in his discussion of song structure.

Many musicians and educators will be alarmed by Hewitt’s embrace of electronic music as a teaching tool. There is the widespread fear that relying on software will diminish interest in traditional instruments, and will eventually undermine the very notion of the performer. Schloss and Jaffe address this anxiety in their investigation of “intelligent musical instruments” that decouple the musicians’ gestures from the resulting sounds. While the authors recognize that electronic music poses a grave threat to instrumental virtuosity, they do not regard this as a negative development. They point out that the notion of the virtuoso individual performer and genius composer are specifically western constructions. Other world cultures see music as a collective activity belonging to everyone and no one. Schloss and Jaffe see intelligent musical instruments as opening up western musicians to a similar perspective.

The music world at large can learn further from the listening habits of sample-oriented EDM musicians. The DJs in Thompson’s study speak of listening at three different levels. There is the song level, used for selecting tracks in a club setting. There is the sample level, closer listening while searching for particularly exciting short phrases. And there is the sound level, the most granular of all, used while searching for a particular kick or snare drum sound. These three listening levels could be easily applied to jazz, classical or anything else.

The most important learning resource for the EDM community is the music itself. Jazz musicians have similarly benefitted from easy access to recordings; as the jazz aphorism goes, “All the answers are in your record collection.” A dance musician can move beyond studying recordings, and through sampling and remixing, actively engage with them. The multitrack stems for a variety of well-known pop songs from the Beatles through Kanye West are widely available on the world wide web. In an ideal world, these stems would be standard tools in any music curriculum, for remixing, transcribing or simple listening and enjoying.

User Interface Case Studies

There is no shortage of beginner-oriented, “approachable” music software. However, not all of it succeeds. The following section lists different interface approaches and evaluates their merits.

The keyboard as metaphor

The keyboard has dominated electronic music interfaces since the Telharmonium, and for good reason. It offers a straightforward and intuitive mapping of one key to one pitch. The idea of hitting the key harder to play the sound louder mirrors the familiar analog world. The MIDI standard has entrenched the keyboard metaphor even more strongly. The keyboard paradigm also extends into environments where there is no keyboard involved, for example in the scale entry interface in Auto-tune.

The problem with the keyboard, real or metaphorical, is its strict pitch quantization. The finite pitch set is gentle on beginners, perhaps, but it restricts expressiveness. The blue notes and microtonal nuances we have come to expect from a century of American vernacular and pop music are simply unavailable to the keyboard player. The pitch bend wheel on some keyboards is a step in the right direction, but it is a primitive affordance at best. A guitarist or violinist can effortlessly bend different notes within a chord by different amounts. Electronic music interfaces are sorely in need of a similarly nuanced fine pitch control.

The touchscreen offers some hope in this direction. The iOS app Nodebeat has an exceptionally expressive touch keyboard. Notes played in the center of the keys will sound standard pitches, but the player can also play the entire pitch continuum by dragging from one key region to the next.

Non-Keyboard Interfaces

Not every digital music interface uses keyboard input. Electronic instruments and MIDI controllers have been based on non-keyboard instruments like guitar, saxophone, violin, drums and even the accordion. Like the keyboard, these interfaces hew closely to analog reality in their parameters and mappings. It does not take much imagination to have your MIDI violin map fingerboard position to pitch. The ubiquitous Akai MPC sampler, mimicked in many subsequent devices, is essentially a set of small drums played with the fingertips. The relationship between hitting a sampler pad and hearing a sample played back is obvious, visceral and appealing to our intuition.

What if you want to leave the acoustic instrument paradigm entirely? You are suddenly confronted with a serious difficulty: you must determine the mappings from gesture to sound entirely from scratch. The past century has seen a lot of fascinating experiments in non-traditional control schemes, from the Theremin onward, but none of those devices has found widespread use. The hegemony of the keyboard (and other acoustic instrument metaphors) remains substantially unchallenged.

This is not for a lack of trying among experimental interface designers. They have tried motion sensors, touch-based controls, piezoelectric pickups attached to every conceivable object, and even, in Alvin Lucier’s case, direct readings of brainwaves. However inventive these interface schemes are, however, any musician wishing to learn such a scheme is faced with a heroic learning challenge. Before any expression is possible, the musician must understand the device’s idiosyncratic mappings between gesture and sound. Furthermore, the audience must go through this learning process as well; it is quite unsatisfying to watch a performance without being able to connect the performer’s actions to the sounds produced. Morton Subotnick laments that once the gestures in his stage pieces became excessively abstracted from the sounds they triggered, it would have made no difference if he had just played a tape of the desired sounds and had the performer mime along. It is no wonder that interface designers keep returning to drums and keyboards.

Interface designers remain undaunted. Currently, most of their creative energies are directed at various motion-capture systems, helped by the availability of the inexpensive Microsoft Kinect. But as interesting as motion capture is as a technological novelty, it is doubtful that it well ever displace the keyboard or sampler pad. The difficulty is the lack of haptic feedback. In a nutshell, motion capture systems don’t push you back. Without physical resistance, it requires extraordinarily disciplined muscle control to maintain accurate positioning. Motion capture works best in dance-oriented video games, where the player is imitating a specific set of movements. As a music generation method, however, motion is largely an unsolved problem.

Perhaps a motion capture standard will someday catch on the way MIDI did, and Kinect-like controllers will become as ubiquitous as keyboards. I am not optimistic. Motion capture defies bodily intuition. There is no instinctive causal relationship between empty-handed movement and sound generation. Usually it is the sound that inspires the movement. But perhaps I am excessively pessimistic, and that some future music technologist will prove me wrong.

Graphical Scores

The graphical score long predates software abstractions of music. Iannis Xenakis was one of the major innovators in the field. Though the music itself is difficult, Xenakis’ drawing of “Metastasis” is a beautiful work of art in its own right. Brian Eno’s “Music For Airports” includes an attractive graphical score on the back of the album cover. Since a DAW or MIDI sequencer display is effectively a form of graphical score, it seems logical that drawing and graphic design could become a direct form of musical expression. Thus far, however, there have been few successes.

The earliest graphic score concept to have been incorporated into a working electronic instrument was the ANS synthesizer, invented by Evgeny Murzin in 1938. The initials stand for Alexander Nikolayevich Scriabin, the mystical synaesthetic composer to whom Murzin dedicated his invention. Four decades later, the Fairlight CMI introduced a light pen that allowed the user to draw audio waveforms freehand directly onto a screen. These waveforms could then be played back as synthesizer tones from the keyboard. The system was clunky at best, but it did capture the imagination of musicians like Herbie Hancock and Quincy Jones.

The advent of the touchscreen has resulted in an explosion of graphical music interfaces. Ning and Zhou are the designers of a tabletop music creation system, The Music Pattern, a system similar to the Reactable, but with more of a drawing component. The user draws patterns that map to particular pitches and rhythms, which can then be arranged in rows to form melodies. The system translates patterns into a pitch and timing information, with real-time audio feedback to guide the user’s finger movements. Intriguing though this approach is, it ultimately suffered from the same difficulties as motion capture: the mapping between image and sound was necessarily arbitrary and had to be learned laboriously. While Ning and Zhou aimed to make music creation more accessible to novices, they instead inadvertently created an alternative visual interface for an ordinary MIDI keyboard. While their interface may be attractive and entertaining, it is less approachable than a MIDI keyboard would be.

The idea of controlling electronic sounds using graphics suffers from score-centrism. Writing and drawing come from different parts of the brain than singing and dancing, where music originates. It is counterintuitive to abstractly conceive the music in visual form first, and only hear it afterwards. Furthermore, visual appeal and musical appeal are not necessarily coextensive. As Gérard Pape observes:

Sometimes the pages that are the most attractive visually don’t sound well –­ beauty on a visual level does not necessarily correspond to interest on a sonic or musical level.

Indeed, why should we expect otherwise? Being disappointed that a beautiful drawing does not translate into good music is like being disappointed that it tastes or smells bad. Mappings between graphics and audio must strictly defer to bodily intuition if they are to be intelligible.

User Interface Case Study: the Electric Guitar

The most successful and ubiquitous electronic music interface of all time is the electric guitar, and it has many lessons for the physical interface designer. The electric guitar’s intended purpose was to amplify traditional playing styles. However, this purpose has been almost entirely supplanted by uses undreamt of by the instrument’s inventors. The electric guitar’s lightweight strings encourage wildly microtonal embellishments and multistring bends that would be difficult or impossible on an acoustic instrument. Furthermore, some electric guitars come equipped with a whammy bar that enables the player to effortlessly detune the entire instrument with very fine and nuanced control.

The true source of the electric guitar’s musical impact is not the guitar itself; it is the amplifier. Because the player usually stands close to the amplifier, feedback is a constant danger. Jimi Hendrix and others of his generation had the remarkable insight that amplifier feedback could be a form of musical expression in its own right. Hendrix treated the amplifier itself as the instrument, effectively an analog synthesizer amplifying a modulated electrical signal. While the guitar is the most significant control surface for modulating this signal, it is only one of many — other control surfaces include amplifier settings and effects, expression and effects pedals, e-bows, talk boxes, loop pedals, and MIDI pickups.

The example of the guitar poses questions for other electronic music interface designers: how can a tool fail productively? How can designers build a functioning tool that still leaves the door open to unpredictable use cases? How can space be left for the emergent, the serendipitous, the flaw turned into a virtue?

Dennett argues that virtual environments like composition software need artificial collision detection. While the “real” world is full of rough edges, entropy and chaos, these things need to be inserted into computer programs laboriously and by hand. Computer music lacks the “spontaneous intrusions” of human music — there is no amplifier feedback unless the programmer puts it there. An acoustic instrument is slowly, constantly going out of tune. Even hitting the same piano key at the same velocity produces subtly different sounds each time. Analog synthesizers are sensitive to temperature, humidity and the power coming out of the wall. A MIDI piano note is always the same, unless the programmer goes to considerable effort to write quasi-random algorithms to perform pitch-shifting.

A satisfying musical interaction system has to be noisy and unpredictable, because the noise contains potential new signals. A major part of our creativity is not just creating patterns, but discerning patterns in noise that are not really there. Generations of unschooled rock guitarists have expanded the sonic palette of their instruments because the instrument rewards playful experimentation. The best software should do the same.

A promising example of guitar-like open-endedness can be found in Janet McDowall’s field research in the use of software to teach music to young children. She focuses specifically on a program called MidiPads, which uses a touchpad controller similar to an Akai MPC. The pads can be configured to play tonal sounds or percussion. McDowall notes enthusiastically that the program engages children “in the full gamut of ‘modes of expression’ … listening, singing, playing instruments, composing, notating and conducting.” Furthermore, children find uses for MidiPads beyond conventional “music.” Children are observed acting out stories accompanied by sounds triggered by the MidiPads, effectively turning a music tool into a cinematic sound design tool.

I will conclude this section with the story of Paul DeMarinis‘ attempts to design a touch-sensitive “guitar” controller for synthesizers. Each iteration of his design kept moving closer and closer to the construction of actual electric guitars. DeMarinis even started using leather straps, because the smell evoked the rock and roll fantasy so integral to the guitar experience. How many electronic interface designers think about smell? Perhaps more of them should.

User Interface Case Study: Digital Audio Workstations

The Digital Audio Workstation (DAW) is as ubiquitous a software paradigm as the keyboard is a hardware paradigm. However, like the keyboard, the DAW imposes serious limitations out of the box. DAWs universally employ the metaphor of the multitrack tape recorder. Each voice in a recording occupies its own track, and each track persists for the entire duration of the song. This paradigm is familiar to engineers trained on multitrack tape, which helped ease the adoption of Pro Tools and its ilk into the marketplace. However, younger musicians who never learned tape recording in the first place find it to be an unhelpful metaphor.

A contemporary pop song might accrue dozens of tracks, some containing a single sample or phrase. The management of all of these tracks becomes a significant task unto itself. Producers have been known to hire assistants whose sole job is to keep track of their DAW tracks. Furthermore, the tape-recorder metaphor presumes a clear division between recording and performance. A few experimentalists have created compositions directly from tape, but the process is far too laborious to have achieved much mainstream use. For the most part, tape exists to document the sound of a person playing an instrument in real time.

Digital music production operates quite differently. Many electronic musicians are “performing” by manipulating repeats and effects parameters improvisationally rather than playing instruments. DAWs make such performances awkward by requiring playback to be stopped for many editing operations, and by making it difficult to manipulate loops in real time. Ableton Live is somewhat better than the rest of the field in this regard, since it has a mode specifically for such performances. However, moving between “recording” mode and “performance” mode is still awkward, usually requiring that loops be rendered to raw audio first. DAWs further complicate matters by offering limited control of the granularity of voice aggregation. Jumping from a high level of abstraction (sections) to a low level (audio waveforms) and back can take considerable work and organization on the musician’s part. Yet another novel job description is the “project manager” who manages a producer’s audio bounces, versions of sessions and other associated files.

The DAW’s highest level of abstraction is the song. However, live performers and DJs need to work at the level of the set list. Dancers like seamless flows from one song to the next, and a good DJ will keep the groove flowing continuously for hours on end. Closing a DAW session and opening another takes time, and such breaks in the flow are out of the question for dance music DJs and performers. These artists are obliged to assemble enormous and cumbersome single sessions including all of the tracks from the entire performance’s series of songs.

Even those musicians who work solely in the studio continually share elements between songs. It is tedious to have to continually close and open session files just to duplicate a sample from one to another. Duignan, Noble and Biddle offer an especially astute diagnosis of DAWs’ limitations around theme and variation.

DAWs… provide only primitive abstraction mechanisms in this regard, forcing our participants into a false choice between creating blocks of material that are simply references pointing to other blocks (so that no variation from the original is possible), and creating copies, where any variation is possible (but subsequent changes to the original cannot be propagated to derived blocks).

Using file pointers is convenient and reduces overhead, but it makes keeping track of dependencies quite complex.

Imagine the unfortunate beginner, confronted with the tangled metaphorical history of the DAW. Before one can master Pro Tools or Logic, it is first necessary to substantially master multitrack tape recording, at least at a conceptual level. Then one must account for the differences between the gear being emulated onscreen with the reality of the software “under the hood.” Imagine if a Microsoft Word user had to learn how to set lead type. This is the predicament faced by beginner DAW users. Unfortunately, no one has yet devised a fully workable alternative. Ableton Live’s performance mode is a step in the right direction, but much work remains to be done.

User Interface Case Study: Harmony Space

The network has rich potential as visual metaphor for representing music. The flowcharts employed by Hewitt to illustrate “control flow” of a song are an excellent example. Another inspiring idea comes from Leonhard Euler, who devised created a network representation of tonal harmony. He discovered that if one connects the diatonic thirds and fifths into a lattice, the resulting network takes on the topology of a torus. Harmonic proximity and physical proximity on the torus are one and the same. One could not ask for a more body-friendly metaphor.

Harmony Space is a software extension of Euler’s Tonnetz idea. It uses a flat plane rather than a torus, but the principle is the same. Harmony Space organizes the diatonic pitches onto a hexagonal grid, once again showing harmonic relatedness by means of spatial proximity. In Harmony Space, adjacent notes form diatonic thirds and triads. Chords and scales form distinctive geometric shapes. The user can transpose chords and other patterns by simply moving the shapes around on the grid.

While Harmony Space is an elegant didactic tool, it is only partially useful — by design, it totally neglects rhythm. The authors discuss the difficulty of designing a visualization scheme for rhythm that is as elegant as the tone grid. One ingenious solution to the rhythm dilemma is offered by the Shape of Song visualization project by Martin Wattenburg. His method shows the piece of music as a horizontal line, with arcs connecting repeated passages. Narrower arcs show repeated phrases, while wider arcs show repeated sections. One can get a rich and nuanced sense of musical structure and organization simply by glancing at one of Wattenburg’s diagrams. Perhaps in the future, a clever designer will find a way to marry the Shape of Song with Harmony Space, and an intuitive multidimensional music visualization scheme will be born.

User Interface Case Study: Garageband

Apple’s Garageband software has become the de facto beginner-level music production environment simply because it is included free with all of their desktop computers. Garageband is a feature-limited version of Logic, using the same multitrack tape recorder metaphor as most other DAWs. In addition to the basic recording and mixing functionality, Garageband includes a variety of appealing audio and MIDI loops and software instruments. The loops can be altered by the user in a full-fledged MIDI editor.

Garageband is relatively versatile and accessible, but it has several shortcomings as a tool for beginner self-teaching. The pre-installed loops are well-recorded and diverse, but Garageband offers no suggestion as to how to make good musical use of those materials. The interface does not suggest, for example, that by western pop tradition, loops sound best when repeated two, four, eight or sixteen times. Also, Garageband makes no attempt at showing harmonic relationships. Users are left to trial and error to find musical chord/scale combinations. The program does enable the user to set a global key center, which loops will fit into automatically. But when it comes time to enter individual MIDI notes, users are on their own. Ideally, Garageband’s MIDI editor would suggest to the user which notes would actually sound good, perhaps by means of color-coding, or by snapping to consonant chord tones.

A ten-year-old guitar student of mine is a vivid example of both Garageband’s strengths and weaknesses. After only his third lesson, he tried writing his own song with Garageband, mostly by throwing loops together. While I admire his initiative, his song was jagged and disjointed, lacking any kind of structural logic. It is natural that a first effort would be a mess, of course, but I felt a missed opportunity. Watching other beginners struggle with Garageband has made me realize that the software is not really for novices after all. As the name suggests, it seems more intended toward adult amateurs with previous musical experience, perhaps dads in cover bands, who have some half-remembered knowledge of chord progressions and song forms and who just need a minimum of prodding to start putting together tracks on the computer. Complete beginners need to learn musical fundamentals elsewhere before Garageband gives satisfying results.

The iPad version of Garageband is a better experiential learning tool for the beginner. Its new touch-specific interfaces encourage playful exploration. The program is not trying to be particularly pedagogical; nevertheless, its presets and defaults give valuable implicit guidance. And while iPad Garageband is quite a bit more limited than the desktop version, those limitations are strengths for a beginner’s purposes.

The iPad Garageband guitar interface is an exemplary piece of user interface design, one that deserves to be widely imitated. You can tap out notes on the graphical fretboard, complete with string bends. A profoundly non-musical friend of mine took to the virtual guitar immediately, doing huge multistring bends that would be impossible on a real guitar (and that it therefore would not have occurred to me to try.) In addition to the real fretboard layout, you can also play the guitar in Scales mode. You select a scale, major or blues or Mixolydian mode or what have you. The scale tones will then be the only notes available to you on the fretboard. With no wrong notes possible, you are free to effortlessly explore melodic ideas.

The guitar interface also offers a chord strumming mode, and here the touch interface begins to feel truly magical. The strings are overlaid with vertical rectangles, each representing a chord. Brushing your fingertip across the strings within a given rectangle sounds the corresponding chord. It feels very much like strumming with a pick, except that all of the notes are automatically correct. For whatever key you have selected, Garageband presents an assortment of chords that are either diatonic or part of common rock/pop/blues practice. There is also a slot reserved for the user’s choice of chord. The options are surprisingly varied, including several sophisticated jazz chords. Once you have strummed your chords, you can go into the MIDI piano roll and edit individual notes. An advanced user can rough out a guitar part by strumming, and then refine the harmonies one note at a time in the piano roll.

The keyboards work very much like the guitar. You can play individual notes on a regular keyboard, or you can use the equivalent of the guitar’s strumming mode, where moving your fingertip on a vertical strip produces arpeggios or melodic figures. While the prefabricated patterns are banal, they can be easily customized in the MIDI editor. The violin, cello and upright bass interface has a similar arpeggio/pattern interface, along with a fretboard mode allowing both bowing and pizzicato. The fretboard allows satisfying microtonal slides and vibrato. Scales mode is available as well.

From a pedagogical standpoint, the best aspect of iOS Garageband is the way it handles song structure. By default, song sections are eight bars long. You are free to use any length, but if you fall back on the defaults, all of your sections will be eight bars. Duplicating a section is effortless, which encourages symmetrical song structure. More advanced users are free to introduce idiosyncratic phrase lengths if they wish.

There is certainly room for improvement. The scales mode that is so useful in the instruments would be beneficial in the MIDI editor as well. Beginners would benefit from being locked into a single scale globally by default — they could always switch scale mode off if they wanted chromaticism. Also, it would be useful if the program organized the scales and gave descriptions of how they sound and what they’re useful for. The word “Mixolydian” is meaningless to beginner musicians. It would be better to say, “this scale sounds good in rock, blues, country, and a variety of world musics.” Similarly, it would be useful if the chords gave some indication of their function. Perhaps future versions will include better pedagogical guidance. For now, though, iPad Garageband is perhaps the best entry-level digital music tool on the market.

User Interface Case Study: Propellerhead Figure

Propellerhead is a pioneering software synthesizer company. Their first release, 1998’s Rebirth, was designed to emulate the classic Roland TB-303 bass synthesizer and Roland’s TR-808 and TR-909 drum machines. Propellerhead reproduced the sound of these devices with remarkable fidelity. Unfortunately, they also chose to reproduce the original devices’ impenetrable user interfaces, with primitive step sequencing and clumsy editing tools.

The company’s next major release, Reason, was a substantial improvement because it included a MIDI editor. But the design still relied too heavily on skeuomorphism. As DAWs presume familiarity with multitrack tape, so Reason presumes familiarity with rack-mounted hardware synthesizers. Its onscreen graphics are larded with nonfunctional “realistic” decoration: screws, power cords, labels, vents. It is difficult to distinguish the functional elements from the decorative ones. Furthermore, the functional interface elements are modeled after hardware knobs, buttons and LED displays. While this aesthetic is appealing at first glance, it swiftly becomes an obstacle. The skeuomorphisms occupy valuable screen space, making the usable elements smaller and harder to read. Turning fake knobs with the mouse is needlessly difficult and imprecise. And if, like me, you used software for years before ever even seeing a vintage synthesizer or analog effects unit, the hardware metaphor is totally unhelpful. A simple boxes-and-arrows interface with black text on a white background would work better.

Propellerhead has taken an admirable step forward with its first mobile offering, an iOS app called Figure. It has an appealing simplicity: one lead synth, one bass synth, and one drum machine, with a variety of settings and effects for each. Figure uses no skeuomorphism whatsoever. Its interface is comprised solely of flat-colored polygons and large, friendly text. Everything on the screen is functional; nothing is decorative. Smartphone software forces these kinds of minimalist design choices just by virtue of the limited screen real estate, and Propellerhead has wisely chosen to turn that limitation into a strength.

Figure is intended to give the novice user a maximally intuitive and effortless input scheme. Loops play automatically, and the user alters and manipulates them by dragging across the touchscreen. A loop can be broken up into more or fewer rhythmic elements by dragging up or down on a broken wheel graphic. You can select the number of scale degrees available through a similar wheel interface. Selecting the actual scale degree, modifying its loudness, and manipulating effects parameters are all performed by simple dragging within large rectangular screen regions.

This interface, while visually appealing and approachable, has its flaws. Continuous x-y pads map awkwardly onto discrete drum hits and synth notes. It is needlessly difficult to specify a particular beat or pitch — Propellerheads assumes that you will be content with the preset patterns. In fairness, their goal with Figure is different from a designer of pedagogical software. Figure aims to move the user quickly past the sequencing stage quickly and into the filters and effects, where most of the expression in techno music takes place. They succeed in this goal, but it is a shame that the choice of notes and drum beats is so needlessly opaque. Still, Figure’s friendly minimalist aesthetic is inspirational. By limiting the amount of information on the screen, Figure invites the novice to explore, free from option paralysis.

Music Games

Outside of the academy, the richest source of novel interface schemes is the video game industry. The past few generations have been controlling software with joysticks, thumbsticks, buttons, touchpads, motion controls and voice command since childhood. Game controllers are quickly making their way into electronic music, helped along by music-specific games like Guitar Hero. The surprise of seeing a Wiimote or Kinect onstage is rapidly wearing off, and we can expect such controllers to eventually become commonplace in music.

Games like Guitar Hero, Dance Dance Revolution and the like are electronic music interfaces, albeit very simple ones. These games may not enable much creative music-making, but they have a well-documented ability to teach players how to listen actively, like musicians. McDowall and Gower praise these games for having “progressive levels of difficulty and rewards for success and persistence,” which are crucial psychological motivators. The pop-music orientation of music games is invaluable for drawing students into music-learning generally. The authors also observe that in addition to being an enticement into “real music,” pop is worthy of inclusion in the curriculum in its own right. Studies have shown that the skills learned in Guitar Hero or SingStar transfer readily to non-game settings. The authors therefore give an unequivocal endorsement of these games’ inclusion in the music classroom.

Jacob Smith observes that music video games are effective tools for immersing the player in music as an active listener. “[P]laying these games can feel like a genuinely musical experience: the controller is no longer a trigger but a percussion instrument, and the player stops thinking in terms of locking on targets and instead tries to feel the groove.” The “easy” mode in such games is an abstraction of the major melodic and rhythmic events in the song, similar to the reductions performed by music theoreticians. At more advanced levels, the simplified abstractions are progressively filled in until the player must replicate every note or event in the song. This progressively more granular attention to the music is an excellent way to learn to listen like a musician. An avowedly non-musical friend told me that until he played through Beatles Rock Band as Paul McCartney, he had never paid attention to a song’s bassline. Now he hears those familiar Beatles songs with an entirely new informational dimension. No one could have taught him better.

With digital music production taking on many of the qualities of computer games, Smith believes that games offer the best way forward for new and more intuitive interfaces. While the “instrument” interfaces in most music games are simplified, they need not be. It is now possible to play Guitar Hero-like games using a full-fledged MIDI guitar. The game goes beyond simulation into actual guitar pedagogy, using the game framework’s effective psychological motivations.

There is one crucial difference between music games and real music-making, however, and that is the absence of improvisation. The player moves through the song like a train on a track, and the games penalize any variation from the prescribed notes. Not all real-life music is improvisational either, but there is usually some element of personal expressiveness. Not so in Rock Band or Guitar Hero. Mimicry is the only way to play. Joshua Rosenstock recognizes this shortcoming, and has devised a game to try to address it. Working with students at the Worcester Polytechnic Institute, he developed iGotBand, an experimental video game that incorporates improvisation. Players need not reproduce the given note sequences exactly; they are free to use any rhythm, and can interject notes of their choice.

Rosenstock’s game is an admirable attempt at incorporating improvisation into a music game, but he fails to address some basic problems. The improvisation in iGotGame has no bearing on the player’s success or failure. This makes it a nice but meaningless feature. Rosenstock readily admits this to be a problem, and discusses the challenges inherent in turning musical improvisation into a game. Games and music share the verb “to play.” But in both domains, the word play has several distinct meanings. Rosenstock pithily equates play with freedom, and games with rules. He introduces the term paidia, meaning childlike play: spontaneous and unruly. The musical equivalent would be free jazz and other radical improvisational forms. By contrast, there is play as ludus: games with ordered rules, like chess or basketball, and indeed, nearly all video games. The musical equivalent of ludus is classical composition and more formally bound jazz styles like bebop.

Like most other music video games, iGotBand is an example of ludus. The improvisation aspect is a dash of paidia, but this aspect of the game has no bearing on the win condition, and cannot therefore be said to be intrinsic to the experience. We can hardly blame Rosenstock for this shortcoming. How would one possibly devise an unambiguous system of rules for judging improvisation that meet the requirements of ludus? Thelonious Monk’s improvisation is unequivocally better than mine, and mine is unequivocally better than my guitar students. But how could one quantify our relative levels of ability? Rosenstock attempts to address this problem by suggesting that users vote on the quality of others’ improvisation. This, however, does not address the problem, since the votes would be perfectly subjective and arbitrary.

Improvisation might superficially resemble a game, but Rosenstock inadvertently demonstrates how fundamentally incompatible it is with a competitive video game. A better direction for music games would be to remove the win condition entirely. Instead of music games, we could create music tools with game-like interfaces. The Guitar Hero interface could work well as a beginner-friendly production and composition tool. It could present familiar song forms like twelve-bar blues and some suggested riffs that the player could alter at will. The pioneering music game FreQuency included a mode where the player could remix the game’s song library. A further convergence between the gentle learning curve of the game world with the open-endedness of music software like Logic or Ableton Live would invite a great many people into making their own music, rather than just passively consuming it.

Conclusion

Electronic dance and hip-hop musicians are mostly self-taught, learning in ad-hoc peer-to-peer networks or alone. Yet learn they do — global popular culture is dominated by the output of musicians with little or no formal musical training of any kind.

Because music production software is somewhat easier to learn than the violin or guitar, the major challenge of producing electronic music is learning how to listen. This is a skill that generalizes to any kind of music-making. Electronic musicians have the advantage of being able to immediately hear flawless renderings of their ideas, with instant feedback for changes. As with good video games, the dynamic and interactive music software experience is its own motivator and its own psychic reward.

I anticipate that the next generation of beginner-oriented production software will draw not on the tape recorder metaphor, but on the sampler. I could imagine a simplified version of the Session View in Ableton Live, allowing the user to build songs out of musical Legos, dragging and dropping in real time. The user could then open and customize the individual Legos, manipulating smaller Legos to any desired degree of granularity. The customized Legos could then be re-used, transformed, pitch-shifted, time-stretched and so on.

Better visual metaphors for music have yet to be implemented. For example, while the “container” for chords is intuitive, it is also misleading, since the chord is comprised of tones, not a box for them. A better image would be tones as atoms and chords as molecules built from those atoms. The molecular network gets at the relational nature of musical elements. As the molecule becomes a more familiar image, it will become available as an “intuitive” image schema.

The challenge with digital music production is not having ideas or being able to realize them. Spinning out ideas is practically effortless once you master the software. The real problem is option paralysis. Beginners would benefit from a limited set of musical options, gradually unfolding into the full universe of possibilities. Such limitations can guide novices into the best rhythms, melodic structures and harmonic progressions known to traditionally educated musicians. The challenge now is to design software constraints that stimulate creativity, rather than frustrating it.

Bibliography

Blackwell, Alan and Collins, Nick. “The Programming Language as a Musical Instrument.” In P. Romero, J. Good, E. Acosta Chaparro & S. Bryant (Eds). Proc. PPIG 17, pp. 120-130.

Chadabe, Joel. Electric Sound. Pearson, 1996.

Collins, Karen, ed. From Pac-Man to Pop Music: Interactive Audio in Games and New Media. Ashgate, 2008.

• Jesper Kaae. “Theoretical Approaches to Composing Dynamic Music For Video Games.” pp 75 – 91.
• Norbert Herber. “The Composition-Instrument: Emergence, Improvisation and Interaction in Games and New Media.” In Collins 2008, pp 103 – 123.
• Peter Schultz. “Music Theory In Music Games.” In Collins 2008, pp 177 – 188.

Daniel Dennett. “Collision Detection, Muselot, and Scribble: Some Reflections on Creativity.” In Cope, David, Virtual Music, The MIT Press 2001.

Duignan, Matthew; Noble, James; and Biddle, Robert. “Abstraction and Activity in Computer-Mediated Music Production.” Computer Music Journal, Volume 34 Issue 4, Winter 2010, pp 22 – 33.

Gelineck, Steven and Serafin, Stefania. “From Idea to Realization – Understanding the Compositional Processes of Electronic Musicians.” Proc. Audio Mostly 2009, Glasgow, Scotland, 2009.

Gower, Lily and McDowall, Janet. “Interactive Music Video Games and Children’s Musical Development.” British Journal of Music Education, Volume 29, Issue 1, March 2012, pp 91 -­ 105.

Hewitt, Michael. Composition for Computer Musicians. Course Technology, 2009.

• Ch 5 “Dance Music Drum Programming” pp 59 – 74
• Ch 9 “Melody, Bass and Harmony” pp 113 -122
• Ch 14 “Arpeggiation” pp 161 – 168
• Ch 17 “Approaching Structure” pp 185 – 190

Hewitt, Michael. Music Theory for Computer Musicians. Course Technology PTR, 2008.

Katz, Mark. Capturing Sound: How Technology Has Changed Music. University of California Press, 2010.

• “Introduction.” pp 1 – 9.
• “Music in 1s and 0s: the Art and Politics of Digital Sampling.” pp 146 – 176.
• “Listening in Cyberspace.” pp 177 – 210.

Kindall-Smith, Marsha, et al. “Challenging Exclusionary Paradigms In The Traditional Musical Canon: Implications For Music Education Practice.” International Journal of Music Education, 2011.

Lähdeoja, Otso; Navarret, Benoît; Quintans, Santiago; and Sedes, Anne. “The Electric Guitar: An Augmented Instrument and a Tool for Musical Composition.” Journal of Interdisciplinary Music Studies, Fall 2010, volume 4, issue 2, art. #10040203, pp. 37-54.

Lakoff, George and Johnson, Mark. Metaphors We Live By. University Of Chicago Press, 2003.

Magnusson, Thor. “Designing Constraints: Composing and Performing with Digital Musical Systems.” Computer Music Journal, Volume 34, Number 4, Winter 2010, pp 62 – 73.

McClary, Susan. “Rap, Minimalism and Structures of Time in Late Twentieth-Century Culture.” in Daniel Warner, ed, Audio Culture, Continuum International Publishing Group, 2004, pp 289 – 298.

McDowall, Janet. “Music Technology: a Vehicle for Young Children’s Learning.” Australian Journal of Music Education, no. 2, 2008.

Ning, Cong and Zhou, Steven. “The Music Pattern: a Creative Tabletop Music Creation Platform.” Computers in Entertainment, Volume 8, Issue 2, December 2010, Article 13.

Rosenstock, Joshua Pablo. “Free Play Meets Gameplay: iGotBand, a Video Game for Improvisers.” Leonardo Music Journal, Vol. 20, pp. 11–15, 2010.

Saville, Kirt. “Strategies for Using Repetition as a Powerful Teaching Tool.” Music Educators Journal, 2011 98: 69

Schloss, Andrew and Jaffe, David. “Intelligent Musical Instruments: The Future of Musical Performance or the Demise of the Performer?” Interface, 22:3, 1993, pp 183-193.

Smith, Jacob. “I Can See Tomorrow In Your Dance: A Study of Dance Dance Revolution and Music Video Games.” Journal of Popular Music Studies, Volume 16, Issue 1, April 2004, pp 58–84.

Snyder, Bob. Music and Memory: An Introduction. MIT Press, 2001

Thibeault, Matthew. “Wisdom for Music Education from the Recording Studio.” General Music Today, 20 October 2011.

Thompson, Paul. “An Empirical Study Into The Learning Practices And Enculturation Of DJs, Turntablists, Hip-Hop And Dance Music Producers.” Journal of Music, Technology & Education, Volume 5, Number 1, pp 43 – 58.

Vickery, Lindsay. “The Evolution of Notational Innovations from the Mobile Score to the Screen Score.” Organised Sound 17, 2012, pp 128­ – 136.

Wilkie, Katie; Holland, Simon; and Mulholland, Paul. “What Can the Language of Musicians Tell Us about Music Interaction Design?” Computer Music Journal, Vol. 34, No. 4, Pages 34-48

Wise, Stuart; Greenwood, Janinka; and Davis, Niki. “Teachers’ Use of Digital Technology in Secondary Music Education: Illustrations of Changing Classrooms.” British Journal of Music Education, Volume 28, Issue 2, July 2011, pp 117 -­ 134.

I was motivated to create a surround remix of a Beatles song by hearing the Beatles Love album in class.

I chose “Here Comes The Sun” because I have the multitracks, and because I heard potential to find new musical ideas within it. Remixing an existing recording is always an enjoyable undertaking, but the process takes on new levels of challenge and reward when the source material is so well-known and widely revered. Much as I enjoy Beatles Love, I feel that it didn’t take enough liberties with the original tracks. I wanted to depart further from the original mix and structure of “Here Comes The Sun.”

The remix is a well-studied musical phenomenon. However, there has been very little study of the aesthetic qualities of surround sound in music. Most of the extant writing is technical in nature. For surround aesthetics, I drew mainly on our class discussions, and on studies of surround sound in film.

Surround Theory

Why mix in surround? Owsinski lists some of the aesthetic arguments. There’s the obvious fact that the added spatial dimension creates another avenue for conveying musical information. There are more subtle factors as well. Surround gives enhanced sonic clarity, since the spatial separation of voices lets the brain distinguish between them more clearly. Also, there’s more of a feeling of spaciousness without introducing artificial reverb and its accompanying diffusion.

All of these technical advantages aside, Kerins believes that surround obtains its power from a much more primal source, our memory of being in utero:

[H]umans begin life in the sonic environment of the womb, where they can hear but do not see [and] hearing is literally a result of movements in the air around us, giving sound a physical presence implying both nearness and contemporaneousness that image does not have. Both lines of reasoning suggest that ‘surround sound,’ which places more speakers around the auditorium (more physical presence) to envelop listeners with sound (as if in a womb), should enhance sound’s inherently intimate nature and promote immersion.

All mixes aim to maximize immersion; working in surround gives an automatic advantage.

Concert Realism, Hyperrealism and Surrealism

There are three major approaches one can take to music production. Concert realism strives to recreate the experience of the concert hall with the greatest fidelity. Hyperrealism is an attempt to go beyond reality, to create greater instrumental presence or richer sound than was actually present, while still conveying a realistic feeling. And surrealism dispenses with the real world entirely, creating a soundscape that could not physically exist outside of the recording. The Tonmeister tradition values concert realism, as do most jazz and showtune recordings. Rock and pop music from the Beatles onwards usually favors hyperrealism. Sometimes the hyperrealism is superficially similar to concert realism, with EQ, compression and the like used subtly to enhance a mostly “realistic” sound. For example, Neil Young’s Harvest and Harvest Moon albums are meticulously mixed to give the impression of a straightforward document of the band playing in an intimate setting. The Beatles became famous for their blend of overt hyperrealism and even more overt surrealism, using sounds that were conspicuously altered, distorted and otherwise unphysical. Their approach has become the de facto pop standard.

“Here Comes The Sun” is comparatively straightforward as late-period Beatles recordings go. Nevertheless, it has its hyperrealist and surrealist touches. The acoustic guitar is the dominant sonic element, giving the song a pastoral quality. However, the Moog synth creates a competing science-fictional feel, especially since it has a different tone every time it appears. The strings are close-miked and compressed, in keeping with the Beatles’ usual practice, making them sound almost like a Mellotron. And the entire track is vari-speeded slightly fast. Pollack observes that “[t]he vocal parts sound as if all sung by George on overdub, with backing vocal parts used here primarily for their ‘bold font’ highlighting effect.” While Paul McCartney sings the high harmony parts, he blends into Harrison’s tone to the point of disappearing.

Surround sound can be used for realism, hyperrealism and surrealism. For realist productions, the performers will generally be in the front speakers, with reverb and reflections in the rear speakers. These environmental sounds are generally captured live via the same microphone setup that records the performance. Alternatively, the mix might place the listener in the center of the band or orchestra, though this is more of a hyperrealist approach. Surround creates unprecedented opportunities for wild surrealism, though this potential remains largely unexplored outside of a few experimental recordings.

For my own surround mix, I opted for a mixture of hyperreal and surreal elements. I hewed to tradition in placing the vocals and other foreground sounds in the front, and more atmospheric sounds in the rear. However, I also added surrealist touches, for example, randomizing the panning of the handclaps so they roam freely around the sound image.

Film Theory

Little has been written about the aesthetics of surround sound in music, due to the format’s comparative rarity. However, surround sound is ubiquitous in movie theaters and increasingly common in home theaters as well. Film theorists have begun in earnest to examine the capacity of surround to convey artistic meaning. While their insights into the interplay of sound and image necessarily have limited application to music, there is enough overlap to merit some discussion. It is no accident that filmmakers first seriously embraced multitrack sound in the context of musical films like Woodstock and Tommy. Kerins explains that these films aimed to create “a sort of participation, a communication between the audience shown in the film and the audience in the movie theater. The space of the film, no longer confined to the screen, in a way became the entire auditorium, via the loudspeakers that broadcast crowd noises as well as everything else.” It is also no accident that Disney’s Fantasia was a pioneering surround experiment. These films all aimed to create an otherworldly, transporting experience, rather than a “realistic” one.

Information Overload

In conventional narrative film, the surround speakers rarely draw attention to themselves. Dialog, foleys and music largely play from the front channels, with atmosphere in the side and rear. The only time that narrative film puts foreground sound into the surrounds is to overwhelm the audience with more sonic information than they can follow, to create intensity, surprise or anxiety. As Kerins puts it:

[T]he surround channels are particularly well suited to representing danger precisely because they portray the unseen… While a theoretically limitless number of sounds can be used in the creation of a soundtrack, perception has much stricter limits. Psychoacoustic research shows that humans can only pay attention to a limited number of sounds at once; re-recording mixers know this and hence shape their soundtracks to focus audience attention on only two (or at most three) perceived aural objects at a time… [Surround sound’s] discrete channels make it possible for audiences to hear more sounds at once; the limitations described above beg the question of how useful that capability is if those audiences can only process a small fraction of the sounds they are hearing. Occasionally, filmmakers may want a mix to include more sounds than an audience can process, since this strategy creates particular emotions… Gore Verbinski’s The Ring (2003) at one point mixes a child’s voice into all five channels simultaneously so that it cannot be associated with a single location. In this scene, the lead character is recalling something her son had said to her, and it is his voice that plays all around the auditorium. The effect is to add an ethereal, voice-in-the-head effect that not only fits the eerie tone of the horror film but also helps code this bit of dialogue as ‘not-really-there,’ especially in contrast to the tightly localized, front center channel-mixed voice of the mother that immediately follows.

Of course, anxiety is not the only emotion that surround sound can evoke. It can also create a feeling of interiority, of being inside a character’s head, the sonic equivalent of the POV shot. When we hear in surround, we hear as the character does, with sounds coming from all directions, not just the front. This feeling of interiority is a very valuable one for music; what is a recording for, if not to put the listener inside the head of the performer or composer?

The Exit Sign Effect

Filmmakers are generally reluctant to put too much foreground information in the surrounds for fear of the “exit sign effect” — by drawing our attention away from the screen and toward the viewing environment, surround sound can pull us out of the movie. As Kerins observes: “Historically, technologies intended to ‘put the audience in the movie’ have often had precisely the opposite effect. 3-D is an excellent example: the polarized or two-color glasses needed to create 3-D images constantly remind viewers that they are only spectators in a theater.” Music has no exit sign effect — consciousness of the visual environment does not distract meaningfully from the experience. We are already accustomed to filtering out visual distractions when we want to pay attention to the music; we simply have to close our eyes.

Music as Dreaming

Benzon conjectures that music, at its best, is a kind of waking dream. In peak musical experiences, whether playing or listening, people often report that they “stop thinking.” Benzon observes that you don’t actually stop your brain activity in these situations. Quite the opposite is true; music-making or listening requires your brain to fire on all cylinders. So what is stopping? Benzon identifies it as your internal narrator, the module of your brain that creates your social self-consciousness. This module also gives you the ability to create explicit narrative memories and to imagine the future. This narrator module is not a specific anatomical region of the brain; rather, it is an emergent process resulting from the interaction of many brain regions.

During peak musical experiences, you stop thinking about the past, the future, and your own motivations and intentions. You simply exist in the moment, fully absorbed by your bodily sensations. This is probably the same mental state that most animals inhabit all of the time, and it’s the one you experience in dreams. Sagan hypothesizes that dreams are the lizard-like parts of our brains exploring and making sense of the neocortex. As for the sense of floating and flying that music can evoke, Benzon notes that you frequently experience these feelings in dreams, a further hint that dreaming and music are related. It’s possible that the brain activities producing your social self are connected to the ones maintaining your sense of bodily orientation and location. When you suspend one, you suspend the other. Surround sound can make the dreamlike qualities of music all the more vivid and intense. Rather than attending to a particular location in space, the listener is immersed in the internal space of the music.

I aimed to create a “dream” version of “Here Comes The Sun.” The song already occupies two different realities, the pastoral one implied by the acoustic guitar and simple lyrics, and the surreal one implied by the synthesizers. I wanted to bring the surreal aspect more to the forefront, by making the synths more prominent, by removing guitar and by adding vocoder and delay.

Why Remix the Beatles?

Rock fans revere their favorite albums as sacred texts. Beatles albums are particularly prone to this kind of iconic worship. Electronic and hip-hop musicians view their favorite recordings quite differently. We dig the crates searching for raw material for further creative work. We regard sampling, remixing and mashing up tracks to be the sincerest form of homage. There is no better way to get inside a recording than to remix it. The process of considering alternative mixing, editing and effects decisions forces you to engage in the active and analytic listening called for by Moylan. My own understanding of and admiration for the Beatles has deepened profoundly since I began to actively engage their material as a source of my own music.

Remixing the later Beatles albums feels particularly appropriate because they are more like electronic music than straightforward rock. The advances in recording technology that gave the late Beatles albums so much of their imaginative sweep also contributed to their feeling of alienation. In the early years, the band recorded by getting together in a room and playing live to single-track tape. By the end, however Paul McCartney could use multitracking to play every instrument on “Back In The USSR” and “Birthday”, as if he was Prince recording “When Doves Cry.” Many of the later Beatles songs can hardly exist outside of the recording medium. “Tomorrow Never Knows” is a pure studio concoction built around tape loops, essentially an analog techno song. The ending of “Strawberry Fields Forever” is more like Aphex Twin than Chuck Berry. And the Beatles were enthusiastic early adopters of the Moog synthesizer and the Mellotron.

Given how electronic and futuristic their sound was, it is a shame that the Beatles have never allowed anyone to sample them. Fortunately for would-be remixers, Beatles multitracks can be found circulating on the internet. For now, remixing these stems mostly happens beneath the radar. We can hope that the band’s heirs will eventually release the multitracks into the public domain, and let a thousand remixes bloom.

The Beatles Love

The Beatles Love album is the only remix/mashup project sanctioned by the band. Intriguing though it is, Love merely whets my appetite for alternative Beatles. Giles and George Martin took a largely conservative approach to their mixes by the standards of the electronic dance music community. While there a few genuine mashups and dramatic reworkings on Love, for the most part it consists of the intact originals with some samples of other songs sprinkled into intros and endings.

Jordan shares both my excitement and frustration. Here, he describes the album’s opening sound collage, rich with inspiration.

[A]n upwelling of sound slowly builds to a peak (in fact, it is the final, fading piano chord from ‘A Day in the Life’ played backwards), only to be abruptly cut off by the opening anticipatory chord from ‘A Hard Day’s Night’. That is immediately followed by Ringo Starr’s drum solo from ‘The End’, here looped to become a new rhythm track for ‘Get Back’ with the orchestral ladder from ‘Day in the Life’ showing up in the background, along with crowd noise, making the whole enterprise into a sort of meta-commentary on the fame of the original group.

In a perfect world, this collage would be the starting point for a delirious swirl of new associations and connections between the familiar songs. Sadly, aside from a few other daring combinations and reworkings, most of the album hews closely to the originals. In his Allmusic Guide review, Erlewine observes:

There’s only one cut that has the thrilling unpredictability of a genuine mash-up and that’s a cut that blends together “Drive My Car,” “The Word” and “What You’re Doing,” punctuated with horns from “Savoy Truffle”; a chorus from one song flows into the verse from another, as keyboards and percussion from all three, plus more, come together to make something that’s giddy, inventive and fresh.

[T]he craft behind LOVE is impeccable: it flows as elegantly as the second side of Abbey Road, which is an achievement of no small measure. But there lies the rub: even if LOVE elicits a certain admiration for how Giles and George have crafted their mash-ups, it elicits a greater admiration for the original productions and arrangements, which display far more imagination and audacity than the mixes here.

This is a harsh criticism. Perhaps the Martins are too close to the source material to be able to depart from it. I do not have the audacity to suggest that my own remixing of “Here Comes The Sun” improves at all on the original. But I did aim to depart far enough from the original to entire into meaningful dialog with it.

Even where the remixing is too limited or uninspired, the surround mixing is undeniably and uniformly excellent. Hard-panning instruments into the surrounds plays to the Beatles’ strengths. The spatial separation only flatters the band’s performances, and the carefully crafted sonic qualities of the recordings. By contrast, the Doors surround mix we listened to in class inadvertently laid the band members under the equivalent of harsh operating room lights, and the view was not pretty. The Doors need to be heard as a cohesive unit or not at all. The Beatles, on the other hand, reward close attention to their isolated tracks. The Martins are free to replace the awkward hard panning in the original stereo mixes with thoughtful placement in the surround field, playing up the Beatles’ immersive dreamlike quality.

The Grey Album

A few intrepid electronic music producers have braved the Beatles’ litigious wrath. The most ambitious and irreverent Beatles reworking is Danger Mouse’s Grey Album. Beginning with the acapella tracks from The Black Album by Jay-Z (made widely available by the artist himself), Danger Mouse created new instrumental backings for each song using nothing but samples from the White Album. The result was an internet sensation. Naturally, EMI served Danger Mouse with a cease and desist letter, but this set off a wave of anti-copyright activism across the web that turned Danger Mouse into a bona fide celebrity.

For myself, the Grey Album was an invaluable gateway into Jay-Z’s work. While I had been aware of his work from the radio, I found him off-putting and did not give him much attention. I was drawn into the Grey Album by a lifelong love for the White Album. I was eager to hear the reworked versions of the familiar songs, and was particularly delighted by Danger Mouse’s frequent use of oddities and obscurities — the harpsichord in “Piggies,” the ending to “Cry Baby Cry,” the acoustic guitar from “Mother Nature’s Son.” Jay-Z’s vocals were incidental to my interest at first. But through repeated listening, his emceeing began to grow on me, and eventually I became hooked. Because of his pro-remixing attitude, Jay-Z can also be heard on top of instrumentals sampled from artists as diverse as Radiohead, Brian Eno and Philip Glass.

My remix approach

Much as I admire the Grey Album, I thought it would be more interesting to limit myself solely to sounds found in the original multitrack of “Here Comes The Sun.” I did bring in some new effects from Ableton Live. These include a vocoder to create additional vocal harmony; compression to bring particular sounds to the forefront of the mix; and various forms of delay for greater psychedelic flavor.

The original song

Here is a diagram of the multitrack version of “Here Comes The Sun” that was my starting point. Verses are blue, choruses are green, instrumental breaks are orange, the bridge is purple, and the outtro is yellow.

From top to bottom, the tracks are as follows:

• Drums, including a very staccato guitar or synth sound doubling some of the drum fills.
• Bass, very isolated, probably recorded direct.
• Acoustic guitar, probably the guide track for the rest of the recording.
• Strings and synth – I am not sure whether these were combined on the original multitracks, but they were on the version I have.
• Vocals, both lead and backing. As with the strings/synth track, these may have been separated on the original multitracks, but were combined on the one I used.

Verse one is instrumental. The first four bars are guitar only, with the strings and synth entering on bar five. The vocals enter on chorus one. On verse two, the bass and drums enter. The second chorus has a short additional interlude on the end. On verse three, the vocal melody is doubled in the synth. The surreal qualities of the track become fully apparent during the bridge. The synth enters on the second pass through the bridge figure, and has a noticeably different tone on each subsequent pass. The handclaps enter on the second to last pass. The bridge ends on a four bar build leading back into the final verse. With all due respect to George Harrison, I have always felt that this passage is a bit of an anticlimax. The song ends with verse four, chorus four, chorus five, a tag consisting of the second half of the chorus, and the ending, a single pass through the bridge form on guitar only.

My remixed arrangement

I added three sections: a long intro, an interlude between chorus one and verse two, and an extended ending to the bridge.

My intro was built from the repeated bridge figure (“Sun, sun, sun, here it comes.”) I adding a track on each pass: vocals and strings, then synth, then handclaps, then drums. I replaced the four-bar bridge ending with a six-bar loop of the vocal phrase “here it comes” over drums only. Using the vocoder, I reharmonized these vocals into a more dramatic chord progression.

I left verse one more or less intact, aside from some effects added to the guitar and the sampled handclaps looped throughout. I used the same approach on chorus one. I doubled the length of verse two, preceding the vocals with an instrumental section. I felt that the song would benefit from a more aggressive and attention-grabbing sound to the strings, so I highlighted them in the mix and stuttered them rhythmically over the bass and drums. I kept the stuttered strings under the vocals in verse two for greater rhythmic interest and groove.

Under the second chorus, I thickened the vocal harmony with the vocoder. I continued the vocoder into verse three and chorus three. The bridge I left mostly intact, aside from added handclaps and more prominent placement of the synth in the mix. But I once again replaced the final four bars with something musically more active: a sixteen bar spacey breakdown, using Ableton’s Fade To Grey effect on the master channel (filtering out the high and low frequencies and adding long ping-pong delay.) On top of the repeated four-bar guitar figure, I looped a three-bar sample of “sun, sun, sun, here it comes.”

I then gave verse four the feeling of emerging from the clouds, just the vocals, drums and handclaps, with the bass entering halfway through. At chorus four, I had the synth re-enter, with the guitar coming in on the turnaround. I had the strings re-enter for chorus five and the tag. I replaced the ending guitar figure with a final repetition of “sun, sun, sun, here it comes” at half speed, combined with multiple layers of the final cymbal crash, also at half speed. The Fade To Grey effect extends the ending, making it boil off into space.

I performed all of this editing from the multitracks using Ableton Live, which has an easier workflow for remixing than Pro Tools, as well as DJ-specific effects. Once the remix was completed in stereo, I output the stems to Pro Tools. Using the Dolan Studio control room, I fine-tuned the mix, added some limiter and additional delay, and performed the surround panning using the S360 Surround Imager plugin.

My concept for surround imaging was informed by ideas from film sound mixing. I panned the “dialog,” the dry vocals, front and just left of center. I also placed the bass front and center. I treated the drums as the other foundational element, and spread them 270 degrees across the sound field, centered in the front. I centered the more dreamlike vocoded vocal the other side of center from the dry vocal, but spread much more widely, to act as more of an enveloping, dreamlike effect rather than a single source. I spread the dry guitar wide across the left from front to rear, with the wet guitar panned similarly on the right. I decided to treat the combined string/synth track as atmosphere, panned entirely to the rear. The dry strings were located in the right rear for a “realistic” feeling, while the wet strings were spread across the rear, again for dreamlike immersion.

In order to isolate and loop the handclaps, I had to EQ them severely and quantize them on the grid. This made them sound conspicuously artificial-sounding. I decided to push their science-fictional flavor as far as possible, and set them to roam around the surround field at random. Ableton’s Beat Repeat effect, heard on the wet guitar track, also has a randomized aspect. I am attracted to the notion that each time the mix is played or bounced, the claps and guitar will come out differently.

Track listing with effects and panning

Acoustic guitar dry

• Effects: none
• Panning: front left to rear left

Acoustic guitar wet (duplicated from acoustic guitar dry)

• Effects: sixteenth note Beat Repeat, compression, dotted quarter note delay
• Panning: front right to rear right

Drums

• Effects: compression, reverb
• Panning: from rear/center left through rear/center right

Claps

• Isolated from the bridge, looped throughout the song
• Effects: Extreme highpass to remove other instruments, saturator, quarter note delay
• Panning: randomized

Bass

• Effects: multiband compression
• Panning: center

Misc long delay

• Used for the drum fill at 0:18 and the cymbal crash at the ending
• Effects: dotted eighth note delay
• Panning: across front

Strings dry

• Effects: none
• Panning: right rear

Strings delay (duplicated from strings dry)

• Effects: extreme compression, saturated “tape” delay
• Panning: across rear

Vox dry

• Effects: none
• Panning: front left/center

Vox vocode (duplicated from vox dry)

• Effects: vocoder modulated with a harsh-sounding overtone-rich synth; quarter note delay
• Panning: spread widely, aimed at right of center

The extended bridge and ending use the Ableton “fade to grey” effect on the master channel, combining extreme highpass and lowpass filters with ping-pong delay.

Bibliography

Benzon, William. Beethoven’s Anvil: Music In Mind And Culture.

Erlewine, Stephen Thomas. “Cirque du Soleil / The Beatles — LOVE.”

Gunkel, David. “Rethinking the Digital Remix: Mashups and the Metaphysics of Sound Recording.”

Jordan, Mark. “The Beatles ‘Love’ — a DVD-Audio Review.”

Kerins, Mark. Beyond Dolby.

Moylan, Brian. The Art of Recording: Understanding and Crafting the Mix.

Owsinski, Bobby. Mixing Engineer’s Handbook.

Pollack, Alan. Notes on the Beatles.

Sagan, Carl. The Dragons of Eden: Speculations on the Evolution of Human Intelligence.

Very shortly after I concluded my talk, my wife went into labor with our son Milo. Quite a memorable night.

Growing up in New York City, I was exposed to a lot of beatboxing at the background level. The earliest track I can definitely point to as impacting my consciousness was “Make The Music With Your Mouth, Biz” by the great Biz Markie.

Like so many other aspects of hip-hop, beatboxing seems really easy until you try to actually do it. “Real” musicians look down on it, because it’s extremely accessible at the entry level, and because it has popularly been associated with comedy acts. It’s easy to dismiss something like the Fat Boys’ “Human Beat Box.” But we shouldn’t. This is strong, inventive, confident music, no less effective for its playfulness and good-natured humor.

Some scientists at USC put a beatboxer into an MRI machine. You can watch some fascinating and disturbing videos of how the tongue, lips, palate and glottis produce different drum hits in real time. People have probably been making mouth percussion sounds like this since long before the invention of drums. But beatboxing needs microphone amplification to reach full power. By using the bass-boosting microphone proximity effect, Doug E Fresh fills out the rhythm track just fine in “La Di Da Di” with Slick Rick.

Doug E Fresh’s most virtuoso display that I’ve heard is on “Freaks” with Lil Vicious. While I’m disturbed by the sound of a young boy rapping such  filthy lyrics, Doug’s beats are riveting.

I used some samples of Doug E Fresh over loops of NYU’s Buchla synth to create this track:

Former Roots member Rahzel is one of the great beatboxers of his generation.

In keeping with the Fat Boys tradition of beatboxing as comedy, here’s Reggie Watts improvising some hip-hop using a loop pedal.

Finally, enjoy this French dude beatboxing his way through hip-hop history.

There is a popular game, sometimes called Pong, which simulates on a television screen a perfectly elastic ball bouncing between two surfaces. Each player is given a dial that permits him to intercept the ball with a movable “racket”. Points are scored if the motion of the ball is not intercepted by the racket. The game is very interesting. There is a clear learning experience involved which depends exclusively on Newton’s second law for linear motion. As a result of Pong, the player can gain a deep intuitive understanding of the simplest Newtonian physics – a better understanding even than that provided by billiards, where the collisions are far from perfectly elastic and where the spinning of the pool balls interposes more complicated physics.

This sort of information gathering is precisely what we call play. And the important function of play is thus revealed: it permits us to gain, without any particular future application in mind, a holistic understanding of the world, which is both a complement of and a preparation for later analytical activities. But computers permit play in environments otherwise totally inaccessible to the average student.

Dr Sagan goes on to endorse Space War as a great way to learn about the inverse square law of Newtonian gravitation, which endorsement I second enthusiastically.