The app combines randomness and control in an intriguing way. I also like the fine microtonal control it gives you. You can also use it as a MIDI controller for other software, though I haven’t given that a try yet. If you want to try it for yourself and you don’t have an iOS or Android device, you can snag the desktop version, for free no less.

Aside from Nodebeat, the best three iOS music apps I’ve tried are:

• Animoog — a faithful reproduction of a Moog analog synth. Fascinating, wonderful, versatile, but very complex and I haven’t even begun to plumb its depths.
• Figure — a very stripped-down version of Reason with a beautifully minimalist interface, a sense of humor and wonderful sounds. It also has some maddening shortcomings, however, like not being able to save or export your work (unless you hook up a cable to other recording software from your headphone jack.) Also, nice though the interface is, it would be good to be able to more directly edit your patterns. I presume (hope) they’ll be rolling out more of this kind of functionality in future versions.
• Soundrop — more of a toy than a musical instrument per se, but an excellent toy. If you like quasi-randomness in your music, this offers you tons of gratification. Free, well worth monkeying around with.

I haven’t tried some of the big name iOS music programs yet. I’m told Garageband is pretty great, and the Electribe looks pretty interesting. For the most part, the apps I’ve looked at are too limited to seem worth the while compared to serious software like Ableton, Pro Tools, Reason and so on. But I’m keeping an open mind. If you have recommendations, please put them in the comments.

Subotnick has an extremely friendly dog.

The studio is cluttered in the manner of a creative person with a lot of diverse interests and a disinclination to throw things out. The shelves are strewn with software manuals, thick classical scores, computer innards, Mac peripherals of many generations, video and audio tapes, Rodney Greenblat CD-ROMs, books, business papers, and even a module from a first-generation Buchla.

Professor Subotnick shares my love of Stephen Mithen’s book The Singing Neanderthals.

The centerpiece of the studio, the Mothership, is Subotnick’s Buchla 200e. He has it patched with a bewildering tangle of cables. He knows what everything does, more or less, but even after a semester of studying and practicing on a similar Buchla, I still find this patch to be fairly impenetrable.

Check out the retrofuturistic touch keyboard on the right. While the Buchla can be controlled by regular MIDI, Subotnick is much more interested in the Buchla’s continuous-touch controls, which can be mapped to any parameter on the synth. Note that the “keys” aren’t rectangular, they’re hexagons and parallelograms.

Subotnick doesn’t just generate live sounds on the Buchla. He also deploys pre-recorded samples. They’re recorded off the Buchla, but then processed much more extravagantly than is possible live. Subotnick likes to create intricate swoops and dives via simulated doppler effects. Lately he’s also taken to using looped samples of his breakout hit “Silver Apples Of The Moon,” mixing them in with everything else. He triggers his samples from a groovy handmade Livid Block. If you look closely you can see his handwritten markings.

All of the sampled sounds blend together seamlessly, since they all have that Buchla timbre. Live remixing on the fly! Pretty hip.

So here’s Subotnick in action. He’s manipulating some Buchla parameters from the touch keyboard with one hand, and has his other hand on a little bank of sliders and buttons controlling yet more parameters via MIDI. The whole scene reminds me of Doctor Who operating the TARDIS — many of Subotnck’s sounds have that BBC radiophonic workshop vibe, which adds to the impression.

Here Subotnick plays samples from the Livid Block. Some are short, punchy attacks, and others are long and trailing. He can combine any attack with any decay to produce a wider variety of different sounds than the grid of touchpads would normally make possible.

The other key piece of the setup is a Mac running Max For Live. Subotnick uses Live for a variety of purposes: he stores his samples there, records his voice on the fly to use as an envelope controller for the Buchla, deploys effects, routes signal in complex ways, and occasionally even plays “normal” software synths with a conventional MIDI keyboard.

Spatialization of sound is a major preoccupation for Subotnick, and he has a pretty sweet quadrophonic speaker array set up. He also has a mammoth subwoofer, which mercifully he didn’t switch on while we were there, as he prefers listening to stuff LOUD.

To get a sense of what this all sounds like, here’s a recent Subotnick performance:

Let me reiterate the complexity of this whole arrangement. All of the Ableton sounds (the samples, synths and effects) can be processed through the Buchla’s filters and gates. All of the Buchla sounds can be fed through Ableton’s myriad effects, and the audio channels can be endlessly duplicated with different processing on different copies. The possibilities are staggering. And as if this weren’t enough to make me want to step up my game, Subotnick also has an electronic piano in the room, that he uses to practice classical repertoire. For four hours a day. Humbling! I have a lot to learn.

Hear some of my Buchla/Ableton music:

Greg: I’ve been listening to 808s and Heartbreak and Twisted Fantasy. I’m really enjoying them. Far more than I thought I would. I think Auto-tune here is somehow protective for Kanye when he is expressing emotion in a genre where that is not really smiled on. I haven’t quite put my finger on it, but I think the dehumanizing of the human voice is somehow a foil for the expression of inner turmoil. It’s haunting.

Ethan: Yes! Absolutely. The Auto-tune gives Ye a way to be the sensitive, vulnerable singer, as opposed to the swaggering rapper. And I like the similar sonic palettes between 808s and Fantasy, except 808s is sparse and Fantasy is full. And the thing of using tuned 808 kick drums to play the basslines is so hip.

Greg: The hard part for me to wrap my head around is the fact that Auto-tune is a filter, a dehumanizer, and it manages to make Kanye both closer and more human.

Ethan: I have a broader philosophical idea brewing about the concepts of “dehumanizing” and “posthuman” and how they’re really kind of meaningless, at least as applied to music. How can things that humans create be dehumanizing? Everyone involved in the production of Kanye’s albums is human. Auto-tune is a novel way of sounding human, but it’s still human, just like the sound of reverb or EQ or compression.

Greg: Yes — I have similar issues with natural vs. unnatural in general. Humans are natural, therefore everything we do is also natural.

Ethan: I’ve been listening a lot to “No Church In The Wild,” the opening track from Watch The Throne.

Kanye doesn’t use any Auto-tune, he just raps. The interesting thing is that the chorus is sung by Frank Ocean, who’s a perfectly capable legit R&B singer, and they put him through the full Cher effect. At the end of each verse, Kanye and Jay-Z tell Frank to “preach” through the Auto-tune. Curious as to your reaction.

Greg: This track is really something. The animal noises fusing with human with street noise. The bizarre outro — WTF is that? The Auto-tune section kind of hides structurally, in some ways. If the liner notes are to be believed, then the Auto-tune section is actually The-Dream on vocals. [Ethan note: it is Frank Ocean singing; The-Dream co-wrote the song.] The extreme EQ of that section is key, though. The dropping to low frequency moves the preceding music into the far distance and down into the horizon. In some ways it heightens the internal effect in an almost cinematic way. It’s a radical emotional zoom and pan. The fact that it is also Auto-tuned may relate to what we were talking about on Kanye’s earlier albums. The sense that Auto-tune allows for and maybe heightens emotional expression. One would think that it is despite the dehumanization, but maybe the dehumanization allows for the words themselves to become more present? I’m not sure. I’ll keep listening.

Ethan: There’s a tradition in hip-hop that if you have an instrumental that isn’t going to get turned into a full song, you append it to the beginning or end of another track. But usually it’s a funk sample or something, not a weird classical piece.

Greg: It reminds me of the Fiona Apple cover of “Extraordinary Machine” for some reason. It’s flat weird.

Ethan: I don’t know that Fiona Apple song, will have to check it out.

Greg: it’s a Marilyn Monroe cover, of all things.

Greg: Funny that delay is not corny, but reverb is? What’s that about?

Ethan: I think the thing with delay is that it’s technologically newer — tape delay goes back a ways, but tempo-synced digital delay is still pretty fresh and of the present. Also, reverb diffuses the sound, and delay keeps everything nice and crisp. Good point about how the EQ spatializes the track — reverb is considered corny by current pop and hip-hop producers, so either you leave everything bone dry or use delay and EQ for spatial effects.

Maybe the Auto-tune heightens emotion by making the melody totally unambiguous. It gives the sung notes an organ-like clarity and distinctness, and slight pitch nuances get exaggerated into stairsteps and warbles. Also, the filter changes the voice’s upper partials in odd ways that adds to the pathos. The-Dream has done some nice Auto-tune singing on other Kanye material — there’s a song called “Flight School” that I have on a mixtape or something. But it’s nowhere near as hip as “No Church.”

Greg: I’m digging “Made in America” as well. The tone is so unapologetic. How often does “banana pudding” show up in rap? It’s unsettlingly positive in some ways. Nostalgic and wistful. Where’s the Auto-tune?

I was teaching John Adams‘ “On the Transmigration of Souls” today and I noticed some distortion on some of the sampled voices. It’s utterly unnecessary but clearly present. I realized that this is related to our discussion of Auto-tune and filters on the voice. My thought in class was: “Do we live so scared that a naked voice is a thing that can’t speak truth?” I’m not sure I still stand by this sentiment, but there it is.

Ethan: I’ll catch myself putting delay on everything as a matter of course. It takes a lot of discipline to leave things dry. I saw this movie called Jiro Dreams Of Sushi about Japan’s best (and most expensive) sushi chef. All he does is cut fish, put it on rice, add some soy sauce and serve. But he uses the best fish, the best rice, the best soy sauce, the best sequencing of dishes, etc. I like that philosophy of getting good ingredients and not processing them at all.

The authors present CMERS, “a Computational Music Emotion Rule System for the real-time control of musical emotion that modifies features at both the score level and the performance level.” The paper compares CMERS to other computer-based musical expressiveness algorithms, as part of a larger effort to find a complete systematic categorization of all of the emotions that can be expressed and evoked through music.

The authors first conducted a survey of past efforts to categorize emotions, and after meta-analysis of the results, devised a two-dimensional graph. The vertical axis runs from Active to Passive. The horizontal axis runs from Negative to Positive. The Negative/Active quadrant includes such emotions as anger and agitation. The Passive/Positive quadrant includes serenity and tenderness. The authors then paired particular musical devices with each emotion, both compositional and performative. For example, sadness is correlated with slow tempo, minor mode, low pitch height, complex harmony, legato articulation, soft dynamics, slow note onset, and so on.

Having established a rule set linking musical devices to emotions, the authors encoded the rules into a set of MIDI filters. These filters were used to generate computer performances with the desired emotional quality. The authors used computer rather than human performers because they wanted a ground base of perfectly flat affect, and very fine control over performative nuance. (A human performer in a good mood will find it difficult to convincingly convey despair, and vice versa.) Finally, the authors played the performances to students and asked them to locate their emotional response on the two-dimensional graph. They found very strong agreement between the intended emotion of a given piece and the students’ ability to identify that emotion.

I approach the authors’ entire effort with considerable skepticism. They have shown that within a given culture and narrowly-defined style, it is possible to identify broad-stroke relationships between particular musical devices and particular emotions. Within the goals they have set for themselves, they have succeeded quite admirably. But no unambiguous categorical system can possibly capture the bottomless complexity and nuance of emotion. A listener’s reaction to a piece of music will depend heavily on social context, personal history and education, and countless other intangibles. The state of the listener’s digestive tract is at least as important in determining their emotional responses as anything happening between their ears.

The authors focus their research on common-practice era Western classical music. This makes their task easier, since Western classical is centered around scores that easily translate into MIDI, and that follow a comparatively narrow rule set. The authors are conscious of this limitation and discuss applying their system to music of other cultures, with rule sets altered accordingly. But it is not necessary to look outside of America to find music whose features would defy ready emotional categorization. As I type this, I have James Brown in my headphones. He’s screaming in what at first blush sounds like rage and pain. Yet the overall result of hearing him is powerful emotional uplift. His music expresses conflicting emotions simultaneously: joy and anger, tenderness and aggression. That tension and complexity is the main appeal of James Brown’s music for me.

While I support efforts to find a deeper understanding of how music conveys and evokes emotion, I am not convinced that a reductionist approach ultimately contributes much of value. It would be better to embrace the full complexity, attempt to trace as many causal threads as possible, and be humble in the face of the ultimate impossibility of the task. For musicians, meanwhile, the best method for understanding how they can convey emotion to listeners is simply to practice and perform, to be attentive to the mood in the room, and to learn by experience.

Any musician who wants to be competent with digital production tools has to take on qualities of a programmer. Music notation is itself a “programming language” for human musicians, complete with loops and subroutines. Electronic music collapses composition, performance and recording into the same act.

How do you differentiate a “live” electronic performance from playing back canned sequences? One way to make the presentation into an actual performance is to include improvisation, or at least the possibility of it. Morton Subotnick is a good example. He considers his compositions to consist of his synthesizer patches and sequences. His performances, on the other hand, are mostly improvisational, deploying his preset elements as he sees fit in the moment. This is similar to the methods of jazz musicians, spontaneously recombining and hybridizing pre-learned riffs and patterns.

Performance demands a close relationship between gesture and result. Which tools and interfaces are best suited to live computer music? Blackwell and Collins approach the question as scholars of the psychology of human-computer interfaces. Their motivation for studying laptop musicians lies in the way that such non-traditional “end-user” programmers can grant valuable insight into software design generally:

We believe that the study of unusual programming contexts such as Laptop music may lead to more general benefits for programming research. This is because significant advances in programming language design have often arisen by considering completely new classes of user who might engage in programming activity… [E]nd-user programmers should not be regarded as ‘deficient’ computer programmers, but recognised as experts in their own right and in their own domain of work.

An admirable sentiment.

Blackwell and Collins survey the landscape of laptop performance tools. On one end of the spectrum, they place Ableton Live and Reason, (comparatively) user-friendly but inflexible software. In the middle are less user-friendly but more flexible graphical programming environments like Max/MSP or PD. Finally, the far end of the spectrum is occupied by the least user-friendly but most open-ended programming tools, command-line languages like SuperCollider or ChucK. It came as quite a surprise to me to learn that people are performing live with textual programming languages. I had seen ChucK and the like used for composition and sound design, but never on the fly in front of an audience. I was even more surprised by the authors’ mention of Alex McLean, who plays live using a customized version of Perl.

Blackwell and Collins devote a good part of their discussion to a comparison of Ableton Live and ChucK as live performance tools, particularly with regard to onstage improvisation. The authors appear not to think very highly of Ableton. They view its hardware metaphors and strong orientation toward dance music as a priori constraints on the user’s creativity. They grant, however, that Ableton’s narrowness of focus suits its intended use case well. While they are more excited by the limitless possibilitiess of ChucK, they are frank about its shortcomings: there is significant lag between the performer’s action (typing a line of code) and receiving feedback (hearing the resulting sound.) Also, the debug cycle has to be accomplished on stage in midflight. Ableton is tolerant of user mistakes and unintentional moves in ways that ChucK profoundly is not.

Any serious electronic instrument should approach the instantaneous tactile and auditory feedback that acoustic instruments have given us for tens of thousands of years. Ableton passes this test in some of its functionality, and fails it in others. ChucK fails the test completely. Blackwell and Collins recognize this difficulty.

The reader may therefore wonder why any live performer would choose such a challenge as ChucK when set against the comfortable ride offered by Ableton.

Certainly, this reader does.

An aesthetic response would be to embrace the challenge of live coding; the virtuosity of the required cognitive load, the error-proneness, the diffuseness, all of these play-up the live coder as a modern concerto artist.

This is the point where I depart philosophically from the authors. Few people know or care how difficult a piece of music is to perform. Musicians should only be concerned with the emotions they evoke in the listener. If the only emotion being evoked is “wow, that must be hard,” that turns music into an athletic competition and drains it of its meaning.

The authors are concerned by “the representational paucity of programs like Ableton, which are biased towards fixed audio products in established stylistic modes, rather than experimental algorithmic music which requires the exploratory design possibilities of full programming languages.” Fair enough. But when I introduce musicians to Ableton, they tend to be boggled by the possibilities. This is as true for avant-gardists as it is for pop and dance artists. Morton Subotnick uses Ableton extensively, and if he has not exhausted its creative possibilities, it is hard to imagine anyone doing so.

The most valuable piece of musical insight given by Blackwell and Collins is this:

It is an interesting question whether some software structures (recursion, conditional branches) may be adopted in future as part of the conventional listening repertoire for live programming audiences. If this were to happen, then musical notations might evolve to support them.

Here is where the vocabulary of programming has the most to offer musicians. The musical instruction “repeat until cue” has a strong analogy to while and for loops. Conditional loops have been crucial to the work of John Coltrane (as in “My Favorite Things”) and James Brown (in too many songs to list.) Other sophisticated improvisers already use nested recursive loops and self-reference. I could easily imagine exciting improvisation-oriented compositions based on conditional branching, where the network diagram is mapped out ahead of time, but the particular path through it varies with every performance. I join the authors in hoping for continued convergence between the thought processes of programmers and improvising musicians.

Guitar Hero, Rock Band and games like them have done a wonderful service to non-musicians. The games give a good sense of what playing an instrument in a band is like. The interface is simplified, but the overall experience is qualitatively remarkably similar. The games also change their players’ listening habits. A non-musician 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 all those familiar Beatles songs in a new and richer way, and generally has learned to listen like a musician.

There is one crucial difference between the 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 Guitar Hero. Mimicry is the only way to play.

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. The player interacts with an assortment of animated avatars. Each avatar presents a row of colored blocks, representing note sequences to be played on the game controller. By playing the avatar’s note sequence, the player can capture it as a fan. The goal is to collect the most fans. The player need not reproduce the 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, making 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, ranging from chess to basketball, along with nearly all video games. Here the analogy is to classical music, as well as more formally bound jazz styles like bebop. Ludus permits improvisation as well, but within much tighter constraints.

Like other music video games, iGotBand is an example of ludus. The improvisation aspect is a dash of paidia, but again, this aspect of the game has no bearing on the win condition. 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?

Improvisation can certainly be done well or badly. I’m better at it than my beginner guitar students, and Thelonious Monk was enormously better at it than me. But how could you quantify what makes Monk better than me, and me better than my students? I doubt that such a quantification is possible, even in theory. Rosenstock makes a vague gesture in the direction of social networking as a solution, but this doesn’t address the problem. People on the internet would vote for whichever improvisation they preferred according to whatever inscrutable criteria we use to judge any creative work. There would still be no unambiguous win condition that would meet the expectation of a gamer. Improvisation might superficially resemble a game, but Rosenstock inadvertently demonstrates how fundamentally incompatible it is with a competitive set of rules.

A better direction for music games would be to remove the win condition entirely, and turn them into expressive media. 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.

When a student brings a recorded song to me that they want to learn, the first thing I do is load it into Ableton and mark off the different sections with a simple color-coding scheme: blue for verses, green for choruses, orange for instrumental breaks and so on. This enables even non-readers to grasp the overall structure of the song. I then loop a short segment, usually significantly slowed, and have the student repeat it until they’ve attained some proficiency with it. As the student progresses, the loops get longer until they encompass entire sections. If a particular phrase is especially troublesome, I can send the student home with an mp3 of that phrase looped endlessly to practice over.

I can’t overstate the value of using loops of actual songs played by actual musicians, as opposed to metronomes or fake-sounding MIDI tracks. The metronome demoralizes students quickly, and convenient though MIDI is, it doesn’t convey feeling and nuance. Study of the genuine article, with its groove and feeling intact, is a vastly richer and more engaging experience. Also, listening to music loops creates a trance-like, meditative feeling, as fans of repetitive electronic dance music will attest. This meditative state is most conducive to flow, and turns repeated drilling into a pleasurable act.

Saville’s article discusses the value of repetition in music learning, and the challenges of putting it into practice. Repetition is fundamental to all forms of human learning, as the rehearsal of the material causes repeated firings of certain networks of neurons, strengthening their connections until a persistent pattern is firmly wired in place. Young children enjoy the endless repetition of any new word or idea, but for older children and adults, such literal repetition becomes tiresome quickly. Still, rehearsal remains a critical memorization method, especially in the intersection of music and memory. The trick for a successful music instructor is to lead the students through enough repetition to make the ideas stick, without descending into tedious drilling.

The key to effective music learning is “chunking,” breaking a long piece into short, tractable segments. Depending on the level of the students, those chunks might be quite short, a single measure or phrase. Once a series of chunks is mastered, they can be combined into a larger chunk, that can then be combined with still larger chunks until the full piece is mastered. Chunking helps get students to musical-sounding results quickly. Rather than struggling painfully through a long passage, the student can attain mastery over a shorter one, which builds confidence. Furthermore, Saville points out that chunking can help make feedback more immediate and thus more effective:

Experienced music teachers become adept at chunking and sequencing the reassembly of difficult musical passages as a means of solving complex performance problems. By chunking, we eliminate the delayed feedback inherent in a long list of items to be fixed after the performance of a long passage and instead focus on more useful and immediate feedback. Repeating the two most critical measures of a sixteen-measure phrase will solve more problems than the repetition of the entire phrase. Likewise, chunking the three troublesome interval leaps in a four-measure phrase will increase rehearsal efficiency and productivity.

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, immediately after looping a passage, or even better, while the loop is in progress.

Repetitive drilling demoralizes students quickly. The challenge is to find a way to get students to repeat new ideas enough times to master them without boring them to the point of discouraging them. The strategies Saville lists are intended for classical ensemble teaching, but they are equally valid for jazz, rock, country and pop. Some of his recommended methods include:

• Call-and-Response Repetition — the teacher leads by example, without explaining the how or why, and students must use their own ingenuity to imitate.
• Performer-Switching Repetition — repeating a phrase with different students playing on each pass.
• Guided Discovery with Repetition — asking students to describe what they’re doing.
• Repetition with Addition or Subtraction of Degrees of Freedom — for example, having students perform the rhythm of a passage on a single pitch. I call this exercise the one-note groove and find it very valuable.

In my own music study and teaching practice, two programs have been invaluable in loop-based teaching: Transcribe by Seventh String, and more recently, Ableton Live. Both of these programs easily enable you to isolate sections of recordings, loop them, and alter their tempo. Transcribe is a fairly primitive piece of software, but it’s perfectly adequate for its stated purpose: helping the user transcribe jazz solos. It works equally well with any other style of music. In addition to its looping functionality, Transcribe can also identify the pitches present in short segments of audio.

Ableton is a full-featured audio production and editing tool. For education purposes, though, its robust looping features are the crucial ones. Ableton has the additional advantage of being able to arbitrarily alter pitch and tempo with minimal digital artifacting.

Coming next week: using drum loops to help students nail down their groove.

Chapman examines the impact that Timbaland has had on popular music production, and what his significance is to the broader culture. While Timbaland himself is no longer the tastemaker he was at his peak ten or fifteen years ago, his sonic palette has become commonplace throughout the global pop landscape.

The first generation of hip-hop producers built tracks around samples of vinyl funk, soul and jazz albums. These samples were imbued with all the sonic ambiance of 1960s and 1970s recording: warm-sounding equalization, reverb, analog compression, and all the small performative imperfections resulting from people playing live in a room. Timbaland uses such samples too, but very rarely. He typically builds his tracks “from scratch,” using drum machines and synthesizers. Timbaland favors the highly artificial sound of the Roland TR-808 and other synthesized percussion sounds. He pairs these sounds with otherworldly synthesizer pads and out-of-context ethnic sounds. For example, in “Get Ur Freak On,” a track he produced for Missy Elliot, Timbaland mixes koto, a tabla beat, a droning synths and American-sounding kick drums and rimshots, a combination that places the song everywhere and nowhere. He adds to the placelessness by dropping in some meaningless snippets of speech in Japanese and Hindi.

Chapman aptly describes Timbaland’s sound as “two-dimensional.” The sounds are bone-dry, without reverb, delay, or any of the other usual methods for giving music a sense of space. Also, there is no extraneous between-note noise; Timbaland’s tracks use a backdrop of total silence. When I was learning Pro Tools, I was urged several times never to allow any silence — to avoid “digital black.” Empty spaces in digital recordings are customarily filled with ambient noise to create the illusion of a continuous recording made by humans in a physical place. Timbaland violates this custom, makes conspicuous use of digital black. The spaces between the beats and fragmented samples are startlingly empty. Furthermore, the spaces are precise enough in their arrangement and duration to be crucial rhythmic elements in their own right.

There is widespread anxiety in the popular music world about the “artificiality” of digital production techniques. Even musicians who make extensive use of software synthesizers, quantization, Auto-tune and the like are often anxious to conceal that fact. In the rock world in particular, significant effort goes into making digital recordings sound “real.” Timbaland is afflicted with no such cognitive dissonance. He puts his techniques’ “fakeness” front and center, even in his treatment of vocalists. The chorus of “Work It,” one of his biggest hits with Missy Elliot, centers around backward-masked lyrics, the least “real-world” sound imaginable. Yet millions of  fans have embraced Timbaland’s seemingly cold and inhuman style, and his songs are a reliable way to get a dance floor moving. How can this be?

Chapman’s assessment is that Timbaland is giving musical voice to the contemporary condition using Paul Virilio’s concept of “telepresence,” which he describes as

the radical realignment of social relations catalyzed by the widespread use of contemporary communication technologies. The notion of telepresence invites us to think about the ramifications of a world in which the privatized virtual space of electronic communication comes to replace the face-to-face interactions that have historically constituted the public sphere… [T]elepresence might serve as a useful analogy for a production aesthetic that, in its evocation of a two- dimensional sonic environment, reinforces the retreat of R&B and rap lyrics from the domain of public interaction to a virtual non-place of private enjoyment.

Chapman finds the “flat, uninflected sonic space of post-Timbaland rap and R&B” to be anti-humanist, lacking interior depth or emotional experience beyond the confines of the body.

As Virilio argues with respect to telepresence, virtuality fundamentally reorders the relationship between near and distant, bringing together private nodes of communication in the same moment that it severs its ties from the local and the public…We must be wary of a posthuman that is so eager to celebrate virtual space that it neglects the accelerating deterioration of concrete space and the bodies that occupy it.

I do not share Chapman’s anxiety. The internet has hardly replaced face-to-face interaction. Our mutual alienation in the posthuman world is a symptom of apartment and suburban living, long working hours in tightly controlled settings, a mobile population and many other social forces that work against communal and familial relationships. The internet goes a long way toward reducing our isolation.

If high-tech dislocation is a fact of our lives, it’s only natural that we would embrace music that speaks to our experience. Timbaland’s music may be conspicuously digital, but it is rarely cold or bleak. If it motivates us to gather together and dance, I see no reason to be suspicious of its supposed unreality or anti-humanism. What could be more warmly human than social dance?

Before “Believe,” Auto-tune was used for its intended purpose: to correct vocal performances in a natural-sounding, transparent way. Cher’s producers Mark Taylor and Brian Rawling discovered that if they turned the Retune Speed setting to zero, it produced the futuristic robot sound we’ve all come to know well. Since they were producing a high-tech dance track, they figured that the robot sound fit the mood, so they kept it in.

I doubt that Taylor and Rawling were the first people to discover the zero retune speed setting, but they were the first to use it on a mass-market commercial recording. To keep other people from imitating the sound, they told interviewers that they had achieved the effect with a vocoder. The music press repeated their story endlessly, so to this day there’s widespread confusion about the difference between vocoder and Auto-tune.

Original question on Quora

There’s no way to separate out the different tracks from a mixed song. If you want the vocals isolated, you need to get your hands on the acapella version of the song. DJ versions of pop and hip-hop singles often include the acapella and instrumental. Every so often a band will sell or give away “stems” — tracks with each instrument isolated. Stems also sometimes leak onto the web. Google is your friend here.

If you can’t get your hands on acapellas, instrumentals or stems, you can still do a lot of creative mashing up. Look for sections that are “in the clear,” where one instrument plays in isolation. Intros, endings and breakdown sections are good places to look for samples. I’m especially fond of laying a funky rhythm section break under a jazz or folk song, for example the breakdown of “1999″ by Prince under “A Hard Rain’s Gonna Fall” by Bob Dylan.

As for how to learn: just do it, do it, do it. The web is loaded with useful tutorials. Find some other DJs and remixers and ask for tips, or collaborate. The beauty of the digital music world is that busting out tracks and sharing them for comments and criticism costs nothing but your time. Don’t be too precious about your ideas. Get your tracks finished and play them for other people as often you can. After you do a couple dozen, they’ll start sounding musical, and after a hundred you’ll have some stuff that you’re proud of. Most importantly: have fun.

Here my recent remixes and mashups, enjoy:

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