Category: Music

Three Observations along the Lines of the Ones I Made Earlier about Dog Poop and Parking[1]

Posted on by Mehmet Vurkaç
  1. If you wishcycle[2], your bicycling-instead-of-driving is canceled out.
  2. If you have a Spotify plan, your posts in support of small or indie artists are canceled out.
  3. If you shop on amazon, your critique of just about any -ism is canceled out.

PS: Why are people wearing chin masks? Outdoors, walking alone, not talking on the phone, with a mask on his chin only… Is it to protect shaving cuts?

[1] As a reminder:

If you leave your dog poop on the African American church’s yard (the one with the “Be a good neighbor. Pick up after your dog.” signs), your BLM sticker is canceled out.

If you park your electric vehicle squarely in or diagonally across the bike lane (taking up a parking space, the bike lane, and part of the right lane), your environmental karma is canceled out. (The diagonal version has become more common in Capitol Hill this fall. People are quitting the parallel-parking process halfway through.)

[2] Both in the five apartment buildings I’ve lived in in Seattle and in all the buildings I visit on campus, people are putting these two items in the recycling bins far too often: plastic bags (classic wishcycling) and burritos (what the…). Congratulations, you’ve ruined another batch. (And a batch is the size of a semi trailer.)

Polymetric Crossrhythm as Aliasing

Posted on by Mehmet Vurkaç

or Why Carriage Wheels in Westerns Appear to Rotate Backwards and What That Has to Do with Global-Southern Music and Digital Signal Processing

There is a great deal of debate in music-theory circles about what the term ‘polymeter’ means. I’m going to ignore this and use my (and a few other people’s) definition. Polymeter, to me, is when two musical streams have the same smallest subdivision in common but have different numbers of that subdivision making up one cycle.

I was just listening to Fodé Seydou Bangoura’s music when I heard yet another delightful polymeter, which I’ll call crossrhythm so that fewer people stop reading this post in anger.

In this crossrhythm, the background meter is some multiple of 3. (Whether it’s exactly 3, 6, or 12 doesn’t matter for the present purpose; it only changes the arithmetic a little, with essentially the same result.

Over this background is a solo that, given the tones and accents, has phrases in groupings of four subdivisions. I call this a polymeter; I think many people call it one type of crossrhythm. More importantly, it is what we call aliasing in digital signal processing (DSP).

Here’s how (and why):

If one stream has groupings of three, like so:

1___2___3___1___2___3___1___2___3___1___2___3___1___2___3___1

and the other has groupings of four:

1___2___3___4___1___2___3___4___1___2___3___4___1___2___3___4

and the former only “looks up” to check where the latter is each time it’s back at 1, then here’s what it sees of the second line:

1___2___3___1___2___3___1___2___3___1___2___3___1___2___3___1

1___2___3___4___1___2___3___4___1___2___3___4___1___2___3___4

which, given only when the base rhythm “looks up” at the other, is like this:

1___2___3___1___2___3___1___2___3___1___2___3___1___2___3___1

1___________4___________3___________2___________1___________4

The act of “looking up” each time the base rhythm gets to one is equivalent to the human eye’s (probably, the neural circuitry’s, rather) rate of perception (sampling). Since we can’t see as fast as the spokes of the wheels on a horse-drawn carriage spin, we see the spokes at each time point we’re able to take a visual sample, just like the first rhythm taking a sort of “downbeat sample” and seeing the second rhythm going slowly backwards: 1, 4, 3, 2, 1, 4, …

If you know DSP, you must have noticed that my example is the opposite of actual aliasing. In signal processing, when the signal we are trying to capture has higher-frequency components than how fast we can sample, we see those high-frequency components folded down to lower frequencies. To match this, the music example should look more like the following.

1___2___3___4___5___1___2___3___4___5___1___2___3___4___5___1

1___2___3___4___1___2___3___4___1___2___3___4___1___2___3___4

However, in this case, the perceived second stream is simple going very slowly, not going backwards the way the spokes do in the westerns. For that, we just need a bigger difference between the reference rhythm and the overlaid one.

1___2___3___4___5___6___7___1___2___3___4___5___6___7___1

1___2___3___4___1___2___3___4___1___2___3___4___1___2___3___4

Now we see the “spokes” slowly turning in the opposite direction: 1, 4, 3, …

When I set out the write this post, I didn’t realize that there would be some cases in which the slow (aliased) rhythmic stream would meet the reference meter without the reversal of direction. Does this happen in aliasing in DSP? It does: Aliased components show up in both positive- and negative-frequency basebands. But that doesn’t seem to answer my question because they combine to form one real-valued low-frequency signal.

I think the answer is that whenever signals (rhythms, turning wheels) are periodic and there is a phase relationship between two such entities, that phase relationship is modulo-2π: If you switch where you look up or down the cyclic waveform, you’ll see the phase shift moving forward or moving backward.

A better answer, perhaps, is that the crossrhythm examples are akin to passband sampling, where a communications signal is modulated up to a band with a lower and an upper bandlimit but the Nyquist requirement is a lot nicer than the usual more-than-doble-the-highest-frequency but simply more than double the bandwidth. In that case, I expect to see the wagon wheels going forward as well as backward, depending on which end of the band we are close to.

My Seven Eras of Music Delivery, Your Qualia, and My Certain Lack of Free Will

Posted on by Mehmet Vurkaç

I was reading someone’s post recently about what they called their seven eras of music delivery and noticed that I also have seven, although mine are different. They are:

  1. the 8-track-tape-cartridge era
  2. the era of the 45-RPM 7-inch vinyl single
  3. the cassette-and-12-inch-LP era
  4. the CD era
  5. the early days of downloading, before the MP3, with the UNIX format .au files
  6. the peak era of downloading: MP3s
  7. the era of streaming and ultra-expensive vinyl

Era 1: My earliest memories of recorded music are of 8-track cartridges that my parents and I listened to in the car. It was on these strange storage devices, the primary feature of which, I was told, was that they could skip from the middle of a song to the middle of another song with the push of a button, that I first heard Santana (off this compilation), Demis Roussos (this exact release, from which the songs I remember best are My Only Fascination and Lovely Lady of Arcadia), The Beatles’ She Loves You, Simon & Garfunkel’s El Condor Pasa and Cecilia, Fredrick Davies & Lewis Anton’s Astrology Rap, The Emotions’ I Don’t Wanna Lose Your Love, and a few selections form the musical Cabaret. I didn’t know any English at that time—I still remember the gobbledygook phonetic lyrics I sang along to She Loves You. (Şilagzu, if you can read Turkish.)

Each of those songs is still magical to me.

Era 2: At the age of 3, I’m told, I wanted the household record player to be placed in my room. At first, I mostly listened to the records of children’ stories my parents had bought for me. (Here’s an image of one, at least until it is sold and the page is no longer there.)

Then, sometime between the ages of 6 and 10, my mother and I once stayed at my aunt and uncle’s boat which was moored at the marina of a hotel on the Mediterranean, outside Antalya. Almost every night, the open-air disco would, at some point, feature the song LE FREAK by Chic. Each night, if it had not already been played while we were sitting at the outdoor disco’s dinner area, I would refuse to go to bed until I heard it. I also had gobbledygook phonetic syllables attached to that song (Frigav). That word happened to be mildly reminiscent of the name of the ice-cream bars you could only get during the intermission at a movie theater: the Alaska Frigo. The aluminum wrapper would send a terrible shock through your teeth.)

I had also taken over my parents’ 7-inch 45-RPM singles at this point: I had two singles by my favorite singer (favorite, that is, until I heard Chic) and one by my second-favorite singer. (I have yet to finish finding all six songs on MP3 or something rippable to MP3. As of early 2025, there’s one to go.)

Then, sometime around age 11 and shortly after my father died of cancer, my mother must have bought some compilation LPs of pop songs because I was suddenly listening to New Order, Shannon, The Romantics, Local Boy, Gary Low, Kajagoogoo, Indeep, Denise Edwards, Fox The Fox, Icehouse, Natasha King, Matthew Wilder, Gazebo, Chris de Burgh, Alphaville, and Madonna.

Some time after that, I went out and bought a few single-artist albums: Hot Dog by Shakin’ Stevens, the eponymous debut of (the band) Nena, and Michael Jackson’s Thriller, with Flashdance following soon afterwards. (I used to longingly stare at Purple Rain and Victory at stores, but those were always too expensive.)

In ninth grade one of our teachers arranged  a Xmas/NYE gift exchange. A classmate gave me the vinyl record of Brothers In Arms. To this day, I am very touched and grateful.

The other recording medium of this era was the cassette tape. And given how difficult it was to afford to buy LPs, most “record stores” primarily relied on another business model. They held only one copy of each record and they would make mix tapes for you from their collection. You would choose the length (and type: Chrome, etc.) of blank tape and pay a little more than the cost of the tape. You could specify everything you wanted to go onto the tape; you could specify some of it and leave the rest to them; or leave it all up to them (preferably after they’d gotten to know your taste). It was one of the ways we found out about music that was new to us (and typically, older than us).

You could also buy albums this way. I paid to have POWERSLAVE recorded onto a cheap cassette and my favorite birthday gift of my whole life is still the dubbed tape of Alphaville’s Forever Young my mom got me.

Era 4: CDs came a few years’ later to my part of the world than they did to the US. My first one was a Glenn Miller compilation, a present from my aunt. I was mesmerized by this shiny object with precise writing printed right on it. I wanted to eat it and worship it. I also remember sniffing it. (It smelled very good.)

My first five CDs still feel miraculous to me—fantastical otherworldly objects. And it continues to make me sad that so many of my friends would, in later decades, say things like “CDs are no good except as coasters.”

I still think they’re beautiful.

Era 5: Before anyone else had heard of downloading songs (that I know of), people doing work using UNIX systems started exchanging songs at some point in the mid-‘90s. This is how I became familiar with Björk (oodles of whose albums I’ve legally purchased since), Young MC, and the brilliant Ode to My Car by Adam Sandler, as well as some unidentified recordings of gamelan. I had to put them on a cassette to be able to listen to them at home. The resulting sound quality was atrocious, whether due to the tape or the .au encoding, I don’t know. By the way, I’m no audiophile. The best and most enjoyable music listening of my life was done on a mono handheld journalist-style cassette player. So, when _I_ think it sounds atrocious, it’s gotta be pretty bad.

Still, the music comes through. The brain makes sure of that. (I read on a discussion board that a music lover uses electronic equipment to listen to music while an audiophile uses music to listen to electronic equipment.)

Era 6: I have never downloaded off the original Napster, but one of the bands I was in, back when I was in three to six bands at any time, was being pirated on Napster (and getting royalty checks, too, from elsewhere—for an Australian movie). We felt pretty good about the Napster part.

Also, because I did not own an Apple device until around 2017, all my MP3s came from ripping my CD collection (and from a friend’s Nomad Zen, fully stocked with music from Jamaica and DRC, that he gave me one day, for reasons unknown). I spent most of 2002 and 2003, especially, ripping my CDs to MP3. Then, my favorite band started putting out MP3-only songs, so I started purchasing them, first at 7digital, with whom I’ve since had an unpleasant experience, and then on Qobuz (named after a Central Asian Turkic instrument, the kopuz).

Back in the early aughts, I also legally downloaded comedy from laugh.com, which seems to have disappeared long ago.

I’m still ripping (and still buying) CDs, though at a much lower rate than 20 years ago. These days, it’s because I prefer to do my own tagging. This not only avoids the typical “correcting” most database companies like to do to Portuguese song titles (which they Spanishize), but with the help of Discogs, I can locate the earliest print in the leading format of the time in the country of origin of the artist and thus know the definitive stylization for the album name and the song titles.

Era 7: I found out about Spotify in early 2008 from a friend who worked for CDBaby. I immediately looked it up. I was getting ready to make an account, but in those days I was still reading every word of every contract, agreement, document of terms and conditions, privacy statement, and such. I don’t remember now what I didn’t like about their policies but I did not make a Spotify account—and it turns out I was right. (Who could have guessed so much evil could come out of Sweden!)

I did stream from Tidal for a bit and then Qobuz briefly as well. I suppose streaming is fine if you’re not obsessed with music in the particular way that I am. For me, streaming was an anxiety-producing experience: What if I missed the name of an artist because I was busy with something else? I would have to go back. That would take away from whatever work I was trying to do and concentration I had managed to have. And what if I liked something so much that I wanted to make sure no merger, IPO, hostile takeover, or license change could take it away from me?

What if there’s so much stuff I like that I can’t function as a proper adult?

And that’s why I still buy physical media and then rip it (or purchase digital files on Bandcamp and Qobuz). I need to control the possibility of what I could listen to at any time. I want that full control right up to the moment I die.

Anyway, how about them vinyl releases? (or, as I heard some people say “vinyls” [yuck]… I just received marketing from Laufey that said “vinyls”… Needless to say I’m not buying that product.)

For a while, I was really happy with the upsurge in vinyl availability. That was back when they still came with download cards.

Have you noticed? The download cards are gone. Now, they really just expect you to pay US$35–65 for a single LP and pay more if you want it digital too. Or maybe they assume everyone is streaming, so this is a non-issue. But even streaming technology is going to be replaced by something else eventually. Maybe it won’t be era 8—maybe it’ll be more like era 15—but the streaming player will soon be replaced by an implant. And maybe it won’t stream from a server at all. Maybe we’ll all get an AI that makes up the music, the biographies and histories, the band and artist names, and everything else based on its reading of our brain waves. If it also controls our input and output ports, we could “interface” with friends who have “the same taste” in music and be discussing two entirely different fake songs, fake bands, or fake genres and not even know it because the two AIs handling our “quality time” together would sensor, filter, transform, and augment whatever the other person is saying to match what each of us would most enjoy hearing. If this sounds dystopian, think about our subjective sensory and affective experiences and how none of us has any idea (and could never have any idea) if the experiences we bond over are, to the other person, what we think they are. The philosophical term ‘qualia’ is a handle for realizing whether the question has any meaning. How could anyone—you, me, or a third party—ever know whether what I experience as the color blue is what you experience as the color blue? Maybe it’s your yellowish orange; maybe it’s your ‘sour taste’ or ‘dull pain’. Probably it’s neither. In any case, where in the chain of my sensory nerves would you have to insert yours to find out?

I don’t think there is any point of insertion at which this would work.

And I think this is similar to—in the frustration it can cause and in the realization it leads to—Gazzaniga’s point about free will: At which point along the chains of cause and effect would you want there to be this fully arbitrary freedom?

Let’s say you decide, as an exercise in free will, to refrain from urinating for as long as possible, resulting in urinating while making a presentation to the board of trustees or at a conference. Now, that would be an act of free will. How many of us are willing to do this?

I’ve always known my answer to the trolley problem. If I were to find myself in the circumstances of the trolley problem, I would be proof against free will. There are two possibilities: I pull the lever; I don’t pull the lever. (If you want to make it more general: I do the thing; I don’t do the thing—I intervene; I don’t intervene.)

If I do the one I believe I would, where’s the free will in that? That action was determined well in advance by the combination of my nature and nurture. After all, I’ve known about it for over a decade. And if I do the opposite, how would that be free will if some subconscious part of me suddenly acts in the opposite way of what I think I would do.

Either way, I clearly end up not having free will. So, maybe let’s not worry so much about the coming era of implants and sensory cocoons, with AIs repainting all our interactions with other entities to make us think we are connecting at a deep level while experiencing arbitrary AI hallucinations. We won’t know the difference.

Portmanteaus from Famous People’s Names

Posted on by Mehmet Vurkaç

My pointless brain has been cooking up portmanteaus of famous people’s names. The following are what I’ve come up with so far.

George Duke Ellington

Buddy Miles Davis

Lil’ Kim Thayil

Ornette Coleman Hawkins

Nat “King” Cole Porter

João Gilberto Gil

Wynton Kelly Rowland

                Mark Kelly Rowland

Geddy Lee Sklar

                Alvin Lee Sklar

                                Alvin Lee Ritenour

                                                Geddy Lee Ritenour

Ben Folds Five For Fighting

John Oliver Sacks

Arundhati Roy Buchanan

Willie Nelson Mandela

Jennifer Lawrence Krauss

Anna Kendrick Lamar

Steve Martin Short

                Dean Martin Denny

                                Steve Martin Denny   

                                                Dean Martin Short

Clark Terry Gilliam

Elizabeth Warren Buffet

                Elizabeth Warren DeMartini

Charlie Hunter S. Thompson

Philip Catherine Zeta-Jones

Carl Jungkook

Michael Spiro Agnew

Woody Allen Ginsberg

                Tony Allen Ginsberg

George Michael Jackson

                George Michael Faraday

Michael Jackson Browne

Elton John Lennon

                Elton John Coltrane

                                Elton John McLaughlin

Jon Anderson .Paak

                Ian Anderson .Paak

James Taylor Hawkins

                James Taylor Swift

Roger Taylor Hawkins

                Roger Taylor Swift

Kim Gordon Lightfoot

Toby Keith Jarrett

                Toby Keith Urban

                                Toby Keith Emerson

                                                Toby Keith Richards

Keith Emerson Fitipaldi

Randy Travis Tritt

Dave Stewart Copeland

                Rod Stewart Copeland

Rick James Brown

                Etta James Brown

                                Rick James Taylor

                                                Etta James Taylor

Debbie Harry Connick, Jr.

                Debbie Harry Styles

Hank Marvin Gaye

                Marvin Gaye Su Akyol

Daniel Hope Sandoval

Paul Simon Le Bon

                Carly Simon Le Bon

Howard Blake Shelton

Elton John Deacon

                Elton John Martyn

Jack Bruce Springsteen

                Jack Bruce Dickinson

Bon Scott Walker

                Bon Scott “Not” Ian

Scott “Not” Ian MacKaye

                Scott “Not” Ian Paice

                                Scott “Not” Ian Gillan

                                                Scott “Not” Ian Anderson

Lester Young MC

                Neil Young MC

                                Paul Young MC

Lester Young Thug

                Neil Young Thug

                                Paul Young Thug

Young MC Solaar

                Young MC Lyte

                                Young MC Eiht

                                                Young MC Ren

                                                                Young MC Hammer

                                                                                Young MC Frontalot

                                                                                                Young MC Hawking

MC Ren & Stimpy

Vanilla Ice-T

                Vanilla Ice Cube

DJ Jazzy Jeff Beck & The Fresh Prince Rogers Nelson

                DJ Jazzy Jeff Buckley & The Fresh Prince Rogers Nelson

Mos Def Leppard

.

.

.

Nina Hagen-Dasz

John Abercrombie & [Figure it out.]

LAST BUT NOT LEAST: Natalie Portmanteau

Some Pesky Subgenres

Posted on by Mehmet Vurkaç

No one dared or wanted to admit it at the time, but Nü Metal and Grunge had quite a bit in common.

What’s my positional framework for this claim?

I’m making this claim from just the simple heavy-rock’n’roll perspective; I don’t even have to go to a global-southern perspective to say this.

In terms of the appearances, geographic origins, and the preferred foundational cultural elements of the bands associated with Grunge in the ’90s and with Nü Metal in the aughts (and late ’90s), most critics I was aware of, as well as I and the other music-obsessed people around me, saw these subgenres of heavy rock as utterly distinct. Perhaps this was because I had lived and continued to live in the PNW. It’s hard to imagine a Portlander in 2005 daring to say Korn and Gas Huffer were very alike in any way, musically or otherwise.

There was always SYSTEM OF A DOWN, whom no one could resist being in awe of, but they were seen as an exception. Here in the PNW, people tended to look down on Nü Metal. Perhaps we were still resentful that Melvins had not become a national phonemenon. (Perhaps most were glad Melvins didn’t inadvertently sell out, as all bands who happen to succeed and live long enough to enjoy it are said to have done.)

Imagine if Kurt hadn’t killed himself. But I digress.

I noticed this aural similarity most when a lesser-known band called The Union Underground became my obsession for a while in the mid-aughts. The artwork (the “aesthetic”) and the timing was pure Nü Metal. The sound, though, was not entirely so. If you ignored the release date and the artwork — few people can do this — it sounded like it came from the heyday of Grunge. What stood out to me musically was not drop-D tuning and a scattering of Hip Hop elements. This was much more closely an offspring of Pixies, Melvins, and Gruntruck than of Shootyz Groove, follow FOR NOW, and Ice-T.

I’m probably an aural purist. Many more people, in my experience, view music as a broader phenomenon. They see the outfits, hairstyles, cover art, and other forms of expression and identity, including ethnicity and lifestyle, as part of what makes an artist Punk and not Pop, Industrial and not Hip Hop. I’m thinking of Avril Lavigne and Consolidated, respectively. Starting with the latter, Consolidated has mostly been considered an Industrial act by fans and promoters. What they do in their music is to use samplers (I know this from meeting and talking to one of them outside the context of music) and to rap. It seems to me there’s some serious pigeonholing of Hip Hop by the industry (if not also the fans) when Eminem is part of Hip Hop without a doubt, but white guys who rap about veganism, feminism, and immigration while criticizing bullying, homophobia, and mysoginy over samples are labeled Industrial rockers, not Hip Hop MCs. If we were honest, we would at least, then, include PUBLIC ENEMY in the Industrial bucket. But no, it’s all about your race, not your lyrics, instruments, or style of music.

In the case of Avril Lavigne, I keep trying to find a song of hers that sounds like Punk Rock to me. It’s the same with the “punk idol” of my generation, Billy Idol. He sneers. He was in Generation X, who sang about drinking and stuff. He wears spikes and studs, maybe even a Mohawk. He must be punk, right?

Heck, I like several of his songs; I totally enjoy BLUE HIGHWAY, DAYTIME DRAMA, EYES WITHOUT A FACE, REBEL YELL, and CRADLE OF LOVE.

I just don’t think those songs have anything to do with Punk Rock the genre. And it’s not that I don’t count it if it’s not by Sex PisTOLS, X-Ray Spex, SUB HUM ANS, or CRASS. I’m happy to include The Stranglers, The Jam, and pre-Punk punky bands like The SONICS, DEATH, MC5, and New York Dolls (heck, Green Day, too) among what I consider “punk”… (though I draw the line at that blinky band).

And Punk Rock is an excellent example of how much lifestyle and philosophy matter. It could be a way to pursuade me that I’m wrong. I realize there’s more to punk than distortion, speed, and some sort of a British working-class accent, whether real or fake. Punk is DIY. Punk is community. Punk is—no, briefly was nonconformity. Videos of the very early days of punk reveal people in myriad creative DIY garb that reaches far beyond safety pins, fishnets, and dyed glued hair. You see sparkly dresses and garbage-bag dresses, both groups fully integrated with the earliest and less conspicuous users of safety pins—out of necessity, not fashion.

So… Did The Union Underground play any Grunge? I say they did, and to a notable extent. Did Billy Idol, Avril Lavigne, or Miley Cyrus make any Punk Rock? They probably did at some point, but I haven’t heard it yet. Are they punks? I don’t know. Since Fat Mike opened a punk museum in Vegas, it doesn’t even matter. Who would have thought LINKIN PARK would have the final word.

Anyway, what made me think of this stuff all over again was listening to VERMILIOIN PT. 2 on SlipknoT‘s awesome VOL. 3: (THE SUBLIMINAL VERSES). I don’t think that song counts as Metal of any kind except probably Grunge.

Herbie Hancock's Chameleon's BPM graph from the Android app 'liveBPM' (v. 1.2.0) by Daniel Bach

Listening to music seems easy.

Posted on by Mehmet Vurkaç

Listening to music seems easy; it even appears like a passive task.

Listening, however, is not the same as hearing. In listening, i.e., attending, we add cognition to perception. The cognition of musical structures, cultural meanings, conventions, and even of the most fundamental elements themselves such as pitch or rhythm turns out to be a complex cognitive task. We know this is so because getting our cutting-edge technology to understand music with all its subtleties and its cultural contexts has proven, so far, to be impossible.

Within small fractions of a second, humans can reach conclusions about musical audio that are beyond the abilities of the most advanced algorithms.

For example, a trained or experienced musician (or even non-musician listener) can differentiate computer-generated and human-performed instruments in almost any musical input, even in the presence of dozens of other instruments sounding simultaneously.

In a rather different case, humans can maintain time-organizational internal representations of music while the tempo of a recording or performance continuously changes. A classic example is the jazz standard Chameleon by Herbie Hancock off the album ‘HEADHUNTERS’. The recording never retains any one tempo, following an up-and-down contour and mostly getting faster. Because tempo recognition is a prerequisite to other music-perception tasks like meter induction and onset detection, this type of behavior presents a significant challenge to signal-processing and machine-learning algorithms but generally poses no difficulty to human perception.

Another example is the recognition of vastly different cover versions of songs: A person familiar with a song can recognize within a few notes a cover version of that song done in another genre, at a different tempo, by another singer, and with different instrumentation.

Each of these is a task that is well beyond machine-learning techniques that are exhibiting remarkable successes with visual recognition where the main challenge, invariance, is less of an obstacle than the abstractness of music and its seemingly arbitrary meanings and structures.

Consider the following aspects of music cognition.

  • inferring a key (or a change of key) from very few notes
  • identifying a latent underlying pulse when it is completely obscured by syncopation [Tal et al., Missing Pulse]
  • effortlessly tracking key changes, tempo changes, and meter changes
  • instantly separating and identifying instruments even in performances with many-voice polyphony (as in Dixieland Jazz, Big-Band Jazz, Baroque and Classical European court music, Progressive Rock, folkloric Rumba, and Hindustani and Carnatic classical music)

These and many other forms of highly polyphonic, polyrhythmic, or cross-rhythmic music continue to present challenges to automated algorithms. Successful examples of automated tempo or meter induction, onset detection, source separation, key detection, and the like all work under the requirement of tight limitations on the types of inputs. Even for a single such task such as source separation, a universally applicable algorithm does not seem to exist. (There is some commercial software that appear to do these tasks universally, but because proprietary programs do not provide sufficiently detailed outputs, whether they really can perform all these function or whether they perform one function in enough detail to suffice for studio uses is uncertain. One such suite can identify and separate every individual note from any recording, but does not perform source separation into streams-per-instrument and presents its output in a form not conducive to analysis in rhythmic, harmonic, melodic, or formal terms, and not in a form analogous to human cognitive processing of music.)

Not only does universal music analysis remain an unsolved problem, but also most of the world’s technological effort goes toward European folk music, European classical music, and (international) popular music. The goal of my research and my lab (Lab BBBB: Beats, Beats, Bayes, and the Brain) is to develop systems for culturally sensitive and culturally informed music analysis, music coaching, automated accompaniment, music recommendation, and algorithmic composition, and to do so for popular music styles from the Global South that are not in the industry’s radar.

Since the human nervous system is able to complete musical-analysis tasks under almost any set of circumstances, in multiple cultural and cross-cultural settings, with varying levels of noise and interference, the human brain is still superior to the highest-level technology we have developed. Hence, Lab BBBB takes inspiration and direct insight from human neural processing of audio and music to solve culturally specific cognitive problems in music analysis, and to use this context to further our understanding of neuroscience and machine learning.

The long-term goal of our research effort is a feedback cycle:

  1. Neuroscience (in simulation and with human subjects at our collaborators’ sites) informs both music information retrieval and research into neural-network structures (machine learning). We are initially doing this by investigating the role of rhythm priming in Parkinson’s (rhythm–motor interaction) and in grammar-learning performance (rhythm–language interaction) in the basal ganglia. We hope to then replicate in simulation the effects that have been observed with people, verify our models, and use our modeling experience on other tasks that have not yet been demonstrated in human cases or that are too invasive or otherwise unacceptable.
  2. Work on machine learning informs neuroscience by narrowing down the range of investigation.
  3. Deep learning is also used to analyze musical audio using structures closer to those in the human brain than the filter-bank and matrix-decomposition methods typically used to analyze music.
  4. Music analysis informs cognitive neuroscience, we conjecture, as have been done in certain cases in the literature with nonlinear dynamics.
  5. Phenomena like entrainment and neural resonance in neurodynamics further inform the development of neural-network structures and data-subspace methods.
  6. These developments in machine learning move music information retrieval closer to human-like performance for culturally informed music analysis, music coaching, automated accompaniment, music recommendation, and algorithmic composition for multicultural intelligent music systems.

 

Happy 65th birthday, Deacy!

Posted on by Mehmet Vurkaç

Thank you for Back Chat, Cool Cat, You And I, Spread Your Wings, In Only Seven Days, Misfire, Who Needs You, Under Pressure, You’re My Best Friend, One Year Of Love, If You Can’t Beat Them, Need Your Loving Tonight, and Pain Is So Close To Pleasure, not to mention AOBTD, FWBF & IWTBF. (And, really, every Queen song!).

You really nailed it whenever you wrote one. By the end of my life, I would like to have written one song that’s like one of yours.

Making sentences. . .

Posted on by Mehmet Vurkaç

Winter term has been crazy, although in a good way. I’m teaching six classes this term, all of which are going great (I have awesome students), though one’s a new prep, so I haven’t had time to post here, but I recently found some silliness on my phone that I had come up with while waiting for a train: Making sentences by combining band names.

Here they are:

As Blood Runs Black The Refused Pierce The Veil

Tower of Power Was (Not Was) Built To Spill Ashes

Barenaked Ladies Poison The Well From First To Last

Bring Me The Horizon Within Temptation At The Drive-in

Blonde Redhead Of Montreal Cursed The Only Ones

(And, of course, a band name, all by itself: I Love You But I’ve Chosen Darkness)

Science, Clave, and Understanding

Posted on by Mehmet Vurkaç

When Dr. Eben Alexander defended, in one of the major news magazines, his book (“proof[i]”) [1] about a spiritual non-physical afterlife realm, part of his argument was that he is a surgeon, and therefore a scientist. Surgeons are highly trained, highly specialized people who perform a very difficult and critically important service. It would be absurd not to recognize their value. Their work is without a doubt science-based, but does that make it “science”? (There are, of course, surgeons who publish scholarly work (although, I’ve noticed that in some cases, it’s not about surgery, but on fields as distant as music), and thus function as scholars, and therefore scientists.)

A scientist is not anyone who functions as a professional practitioner of a difficult and science-based field; a scientist is someone who sets up, tests, and evaluates (mostly via statistical data analysis) testable hypotheses (about anything, including the afterlife and spiritual realms, if necessary), and more importantly, does so within the guidelines of rigor, accuracy, objectivity, skepticism, and open-mindedness [2][ii]. It is worrisome to imagine that surgeons are setting up double-blinded clinical trials of surgical practices as part of their work, choosing to apply a known good technique on one patient and an as-yet-unsupported one on another patient. (In other words, I really hope surgeons do not act as scientists.) Maybe they do; I’d like to know, so please give me feedback on this question.

Assuming, though, that they don’t endanger patients’ lives for the sake of science, as we tend not to do anymore, it seems safe to assume that surgeons are highly trained specialists who practice state-of-the-art medicine. In this sense, they are not scientists. They use the findings and results of science in their practical, applied work (medicine). They must, then, fall somewhere between applied scientists and technologists (inclusive).

To say that someone who practices a specialty that is based on scientific findings is therefore a scientist is like saying a sandwich-shop employee is a farmer because they use bacon, lettuce, and tomato in their work. (The fact that surgery is far more specialized does not invalidate the argument.)

The professions that discover, invent, develop, and apply are all different. The roles can overlap—scientists do develop and build new equipment to perform their experiments, but these are not mass-produced. Anything we can purchase repeatedly on amazon or at Best Buy, say, was not made by scientists. It was designed, developed, tested, and manufactured by engineers, technologists, technicians, and other professionals, not by scientists, even if scientists were involved in the early stages. As for applied scientists, including those who work at laboratories, characterizing soil samples, say, or performing tests, they are also highly trained specialists of scientific background who are not doing science at that point. As one XKCD comic suggested [3], you can simply order a lab coat from a catalog; no one will check your publication record. Science is not solely about what you’re wearing or what degrees you have; it’s about what, exactly, you’re doing.

The public’s idea of what science is seems to be “mathy and difficult, preferable done in a lab coat while uttering multisyllabic words you don’t want to see in your cereal’s list of ingredients.” This may be a decent shortcut for pop-culture purposes, but it is not what science really is. I will not go into the inductive-method-vs-hypothetico-deductive-method-vs-what-have-you debate here because there are people who do that professionally, and do it very well. (I have been enjoying Salmon’s The Foundations of Scientific Inference [4] immensely.) What I do want to do is draw two parallels in succession, first from the preceding discussion to explanation and understanding, and from those concepts, to explanations and understanding of clave (in music).

The former has been done quite successfully in Paul Dirac-medal-and-prize-winning physicist Deutsch’s earlier book The Fabric of Reality [5]. I am not concerned here with the bulk and main point of his book, but only with his opening argument about the role of science (explanation) and what it means to understand. Deutsch criticizes instrumentalism because of its emphasis on prediction at the cost of explanation (pp. 3–7). He gives rather good examples of situations in which no scientist (or layperson, for that matter) would be satisfied with good predictions without explanations (p. 6, for example). He does not deny the role and importance of predictions, but argues that “[t]o say that prediction is the purpose of scientific theory is [. . .] like saying that the purpose of a spaceship is to burn fuel” (similar to another author’s argument that the purpose of a car is not to make vrooom–vrooom noises; they just happen to do that as part of their operation[iii]). Deutsch states that just like spaceships have to burn fuel to do what they’re really meant to do, theories have to pass experimental tests in order “to achieve the real purpose of science, which is to explain the world.” (Think about it: Why did we all, as children, get excited about science? To understand the world!)

He then moves on to explain that theories with greater explanatory power than the ones they’ve replaced are not necessarily more difficult to understand, and certainly do not necessarily add to the list of theories one has to understand the be a scientist (or an enthusiast). Theories with better explanatory power can be simpler. Furthermore, not everything that could be learned and understood needs to be: See his example of multiplication with Roman numerals (pp. 9–10). It might be fun, and occasionally necessary to have some source in which to look it up (for purposes of the history of mathematics, say), but it’s not something anyone today needs a working knowledge of; it has been superseded. His example for this is how the Copernican system superseded the Ptolemaic system, and made astronomy simpler in the process (p. 9). All of this is discussed in order to make the point that there is a distinction between “understanding and ‘mere’ knowing” (p. 10), which is where my interest in clave comes into play.

Several “explanations” of clave (sometimes even with that word in the title) that were published in recent years have been of the “mere knowing” type in which clave patterns are listed, without any explanation as to how and why they indicate what other patterns are allowed or disallowed in the idiom. Telling someone that x..x..x…x.x… is 3-2, and ..x.x…x..x..x. is its opposite, so 2-3, and (essentially) “there you go, you now know clave” does nothing towards explaining why a certain piano pattern played over one is “sick” (good) and over the other, sickening (bad) within the idiom.

Imagine if the natural sciences went about education the way we musicians do with clave. A chapter in a high-school biology book would contain a diagram of the Krebs cycle, with all the inputs, outputs (sorry for the electrical-engineer language), and enzymes given by name and formula, followed by “and now you know biochemical pathways,” without any explanation as to how it has anything to do with an organism being alive. I’m flabbergasted that musicians and music scholars find mere listings of clave son, clave rumba, [and . . . you know, the other one that won’t be named[iv]] sufficient as so-called explanations[v].

All of this reminds me of an argument I once had with a very intelligent person. I had said, in my talk at Tuesday Talks, that science is concerned with ‘why’ and ‘how’, not just ‘how’. He disagreed, which I think is because he thought of a different type of ‘why’: the theological ‘why’. I, instead, had in mind Deutsch’s type of ‘why’: “about what must be so, rather than what merely happens to be so; about laws of nature rather than rules of thumb” (p. 11). I would add, about consistency (even given Goedel, because I’m Bayesian like that, and not so solipsistic), which Deutsch mentions immediately afterwards, calling it ‘coherence’.[vi]

I understand that Hume, Goedel, and others have shown us that our confidence in science, or even math, ought not to be infinite. It isn’t. Even in a book like The God Delusion, even Richard Dawkins makes it clear that he is not absolutely certain. Scientific honesty requires that we not be absolutely certain. But we can examine degrees of (un)certainty, and specifically because of the solipsists, we have to ignore them[vii], and be imperfect pursuers of an imperfect truth, improving our understanding, all the while knowing that it could all be wrong.

To that end, I continue to test my clave hypothesis under different genres. Even if it’s wrong, it definitely is elegant.

[1] Alexander, M.D., E., Proof of Heaven: A Neurosurgeon’s Near-Death Experience and Journey into the Afterlife, Simon & Schuster, 2012.

[2] Baron, R. A., and Kalsher, M. J., Essentials of Psychology, Needham, MA: Allyn & Bacon, A Pearson Education Company, 2002.

[3] http://xkcd.com/699/ (last accessed 12/25/2015).

[4] Salmon, W. C., The Foundations of Scientific Inference, Pittsburgh, Pennsylvania: University of Pittsburgh Press, 1966.

[5] Deutsch, D., The Fabric of Reality: A leading scientist interweaves evolution, theoretical physics, and computer science to offer a new understanding of reality, New York: Penguin Books, 1997.

[i] Scientists do not speak of proof; they deal with evidence. Proofs are limited to the realm of mathematics. There are no scientific proofs; there are just statistically significant results, which are presented to laypersons as ‘proof’ because even scientists have quite a lot of difficulty interpreting measures of statistical significance, and the average person has no patience for or interest in the details of philosophy of science.

[ii] The authors of [2] give the following excellent definitions for these precise terms. Accuracy: “gathering and evaluating information in as careful, precise, and error-free a manner as possible”; objectivity: “obtaining and evaluating such information in a manner as free from bias as possible” [Ibid.]. ‘Bias’ in this case refers to the cognitive biases that are natural to human thinking and judgment, such as confirmation bias, Hawthorne effect[ii], selection bias, etc.; skepticism: the willingness to accept findings “only after they have been verified over and over”; and open-mindedness: not resisting changing one’s own views—even those that are strongly held—in the face of evidence that they are inaccurate [2]. To these we can add principles like transferability and falsifiability, and the key tools of double-blinding, randomization, blocking, and the like. Together, all these techniques and principles constitute science. Simply being trained in science and carrying out science-based work is not sufficient.

[iii] I think it was Philips in The Undercover Philosopher, but I’m not sure.

[iv] If you’ve read my post about running into cool people from SoundCloud at NIPS ’15, you’ll know what pattern I’m talking about: the English-horn-like-named pattern.

[v] Fortunately, we do have work from the likes of Mauleón and Lehmann that show causal relationships between individual notes or phrases in different instrumental lines, but since their work and mine, the trend has reverted to listing three patterns, and calling that an explanation.

[vi] Perhaps this paragraph needs its own blog post. . .

[vii] Because, according to them, they don’t exist.

NIPS 2015: Thoughts about SoundCloud, genres, clave tagging, clave gamification, multi-label classification, and perceptual manifolds

Posted on by Mehmet Vurkaç

On December 9th, at NIPS 2015, I met two engineers from SoundCloud, which is not only providing unsigned artists a venue to get their music heard (and commented on), and providing recommendation and music-oriented social networking, but also, if I understand correctly, is interested in content analysis for various purposes. Some of those have to do with identifying work that may not be original, which can range from quotation to plagiarism (the latter being an important issue in my line of work: education), but also involve the creation of derivative content, like remixing, to which they seem to have a healthy approach. (At the same event, the IBM Watson program director also suggested that they could conceivably be interested in generative tools based on music analysis.)

I got interested in clave-direction recognition to help musicians, because I was one, and I was struggling—clave didn’t make sense. Why were two completely different patterns in the same clave direction, and two very similar patterns not? To make matters worse, in samba batucada, there was a pattern said to be in 3-2, but with two notes in the first half, followed by three notes in the second half. There had to be a consistent explanation. I set out to find it. (If you’re curious, I explained the solution thoroughly in my Current Musicology paper.)

 

Top: Surdo de terceira. Bottom: The 3-2 partido-alto for cuíca and agogô. Note that playing the partido-alto omitting the first and third crotchet’s worth of onsets results in the terceira.

However, clave is relevant not just to music-makers, but to informed listeners and dancers as well. A big part of music-in-society is the communities it forms, and that has a lot to do with expertise and identity in listeners. Automated recognition of clave-direction in sections of music (or entire pieces) can lead to automated tagging of these sections or pieces, increasing listener identification (which can be gamified) or helping music-making.

My clave-recognition scheme (which is an information-theoretically aided neural network) recognizes four output classes (outside, inside, neutral, and incoherent). In my musicological research, I also developed three teacher models, but only from a single cultural perspective. Since then, I have recently submitted a work-in-progress and accompanying abstract to AAWM 2016 (Analytical Approaches to World Music) about what would happen if I looked at clave direction from different cultural perspectives (which I have encoded as phase shifts), and graphed the results in the complex plane (just like phase shift in electric circuits).

Another motivating idea came from today’s talk Computational Principles for Deep Neuronal Architectures by Haim Sompolinsky: perceptual manifolds. The simplest manifold proposed was line segments. This is poignant to clave recognition because among my initial goals was extending my results to non-idealized onset vectors: [0.83, 0.58, 0.06, 0.78] instead of [1101], for example. The line-segment manifold would encode this as onset strengths (“velocity” in MIDI terminology) ranging from 0 (no onset) to 1 (127 in MIDI). This will let me look inside the onset-vector hypercube.

Another tie-in from NIPS conversations is employing Pareto frontiers with my clave data for a version of multi-label learning. Since I can approach each pattern from two phase perspectives, and up to three teacher models (vigilance levels), a good multi-label classifier would have to provide up to 6 correct outputs, and in the case that a classifier cannot be that good, the Pareto frontier would determine which classifiers are undominated.

Would all this be interesting to musicians? Yes, I think so. Even without going into building a clave-trainer software into various percussion gear or automated-accompaniment keyboards, this could allow clave direction to be gamified. Considering all the clave debates that rage in Latin-music-ian circles (such as the “four great clave debates” and the “clave schism” issues like around Giovanni Hidalgo’s labeling scheme quoted in Modern Drummer*), a multi-perspective clave-identification game could be quite a hit.

So, how does a Turkish math nerd get to be obsessed by this? I learned about clave—the Afro-Latin (or even African-Diasporan) concept of rhythmic harmony that many people mistake for the family of fewer than a dozen patterns, or for a purely Cuban or “Latin” organizational principle—around 1992 from the musicians of Bochinche and Sonando, two Seattle bands. I had also grown up listening to Brazilian (and Indian, Norwegian, US, and German) jazz in Turkey. (My first live concert by a foreign band was Hermeto Pascoal e Grupo, featuring former CBC faculty Jovino Santos Neto.) So, I knew that I wanted to learn about Brazilian music. (At the time, most of what I listened to was Brazilian jazz, like Dom Um Romao and Airto, and I had no idea that they mostly drew from nordestino music, like baião, xote, côco, and frevo**―not samba).

Fortunately, I soon moved to Portland, where Brian Davis and Derek Reith of Pink Martini had respectively founded and sustained a bloco called Lions of Batucada. Soon, Brian introduced us to Jorge Alabê, and then to California Brazil Camp, with its dozens of amazing Brazilian teachers. . . But let’s get back to clave.

I said above that clave is “the Afro-Latin (or even African-Diasporan) concept of rhythmic harmony that many people mistake for the family of fewer than a dozen patterns, or for a purely Cuban or ‘Latin’ organizational principle.” What’s wrong with that?

Well, clave certainly is an organizational principle: It tells the skilled musician, dancer, or listener how the rhythm (the temporal organization, or timing) of notes in all the instruments may and may not go during any stretch of the music (as long as the music is from a tradition that has this property, of course).

And clave certainly is a Spanish-language word that took on its current meaning in Cuba, as explained wonderfully in Ned Sublette’s book.

However, the transatlantic slave trade did not only move people (forcefully) to Cuba. The Yorùbá (of today’s southwest Nigeria and southeast Benin), the Malinka (a misnomer, according to Mamady Keïta for people from Mali, Ivory Coast, Burkina Faso, Gambia, Guinea, and Senegal), and the various Angolan peoples were brought to many of today’s South American, Caribbean, and North American countries, where they culturally and otherwise interacted with Iberians and the natives of the Americas.

Certain musicological interpretations of Rolando Antonio Pérez Fernández’s book La Binarización de los Ritmos Ternarios Africanos en América Latina have argued that the organizational principles of Yoruba 12/8 music, primarily the standard West African timeline (X.X.XX..X.X.X)

Bembé ("Short bell") or the standard West African timeline, along with its major-scale analog

and the Malinka/Manding timelines met the 4/4 time signatures of Angolan and Iberian music, and morphed into the organizational timelines of today’s rumba, salsa, (Uruguayan) candombe, maracatu, samba, and other musics of the Americas.

Some of those timelines we all refer to as clave, but for others, like the partido-alto in Brazil***, it is sometimes culturally better not to refer to them as clave patterns. (This is understandable, in that Brazilians speak Portuguese, and do not always like to be mistaken for Spanish-speakers.)

Conceptually, however, partido-alto in samba plays the same organizational role that clave plays in rumba and salsa, or the gongue pattern plays in maracatu: It immediately tells knowledgeable musicians how not to play.

In my research, I found multiple ways to look at the idiomatic appropriateness of arbitrary timing patterns (more than 10,000 of them, only about a hundred of which are “traditional” [accepted, commonly used] patterns). I identified three “teacher” models, which are just levels of strictness. I also identified four clave-direction categories. (Really, these were taught to me by my teacher-informers, whose reactions to certain patterns informed some of the categories.)

Some patterns are in 3-2 (which I call “outside”). While the 3-2 clave son (X..X..X…X.X…):

3-2 (outside) clave son, in northern and TUBS notation

is obvious to anyone who has attempted to play anything remotely Latin, it is not so obvious why the following version of the partido-alto pattern is also in the 3-2 direction****: .X..X.X.X.X..X.X

The plain 3-2 partido-alto pattern. (The pitches are approximate and can vary with cuíca intonation or the agogô maker’s accuracy.) "Bossa clave" in 3-2 and 2-3 are added in TUBS notation to show the degree of match and mismatch with 3-2 and 2-3 patterns, respectively.

 

Some patterns are in 2-3 (which I call “inside”). Many patterns that are heard throughout all Latin American musics are clave-neutral: They provide the same amount of relative offbeatness no matter which way you slice them. The common Brazilian hand-clapping pattern in pagode, X..X..X.X..X..X. is one such pattern:

The clave-neutral hand-clapping pattern in pagode, AKA, tresillo (a Cuban name for a rhythm found in Haitian konpa, Jamaican dancehall, and Brazilian xaxado)

It is actually found throughout the world, from India and Turkey, to Japan and Finland, and throughout Africa; from Breakbeats to Bollywood to Metal. (It is very common in Metal.) The parts played by the güiro in salsa and by the first and second surdos in samba have the same role: They are steady ostinati of half-cycle length. They are foundational. They set the tempo, provide a reference, and go a long way towards making the music danceable. (Offbeatness without respite, as Merriam said*****, would make music undanceable.)

Here are some neutral patterns: X…X…X…X… (four on the floor, which, with some pitch variation, can be interpreted as the first and second surdos):

Four quarter notes, clave-neutral (from Web, no source available)

….X.X…..X.X. (from ijexá):

surdo part for ijexá (from http://www.batera.com.br/Artigos/dia-do-folclore)

 

and XxxXXxxXXxxXXxxX. (This is a terrible way to represent swung samba 16ths. Below is Jake “Barbudo” Pegg’s diagrams, which work much better.)

Jake "Barbudo" Pegg's samba-sixteenths accent and timing diagrams (along with the same for "Western" music)

The fourth category is incoherent patterns. These are patterns that are not neutral, yet do not conform to either clave direction, either. (One of my informers gave me the idea of a fourth category when he reacted to one such pattern by making a disgusted face and a sound like bleaaahh.)

A pattern that has the clave property immediately tells all who can sense it that only patterns in that clave direction and patterns that are clave-neutral are okay to play while that pattern (that direction) is present. (We can weaken this sentence to apply only to prominent or repeated patterns. Quietly passing licks that cross clave may be acceptable, depending on the vigilance level of the teacher model.)

So, why mention all this right now? (After all, I’ve published these thoughts in peer-reviewed venues like Current Musicology, Bridges, and the Journal of Music, Technology and Education.)

For one thing, those are not the typical resources most musicians turn to. Until I can write up a short, highly graphical version of my clave-direction grammar for PAS, I will need to make some of these ideas available here. Secondly, the connection to gamification and musical-social-networking sites, like SoundCloud, are new ideas I got from talking to people at the NIPS reception, and I wanted to put this out there right away.

 

FOOTNOTES

* Mattingly, R., Modern Drummer, Modern Drummer Publications, Inc., Cedar Grove, NJ, “Giovanni Hidalgo-Conga Virtuoso,” p. 86, November 1998.

** While talking to Mr. Fereira of SoundCloud this evening at NIPS, he naturally mentioned genre recognition, which is the topic of my second-to-last post. (I argued about the need for expert listeners from many cultural backgrounds, which could be augmented with a sufficiently good implementation of crowd-sourcing.) I think he was telling me about embolada, or at least that’s how I interpreted his description of this MC-battle-type of improvised nordeste music. How many genre-recognition researchers even know where to start in telling a street-improvisation embolada from even, say, a pagode-influenced axé song like ‘Entre na Roda’ by Bom Balanço? (Really good swing detection might help, I suppose.)

*** This term has multiple meanings; I’m not referring to the genre partido-alto, but the pattern, which is one of the three primary ingredients of samba, along with the strong surdo beat on 2 (and 4) and the swung samba 16ths.

**** in the sense that, in the idiom, it goes with the so-called 3-2 “bossa clave” (a delightful misnomer): X..X..X…X..X..,

The "bossa clave" is a bit like an English horn; it's neither.as well as with the rather confusing (to some) third-surdo pattern ….X.X…..XX.X, Top: Surdo de terceira. Bottom: The 3-2 partido-alto for cuíca and agogô. Note that playing the partido-alto omitting the first and third crotchet’s worth of onsets results in the terceira.

which has two notes in its first half, and three notes in its second half. (Yes, it’s in 3-2. My grammar for clave direction explains this thoroughly. [http://academiccommons.columbia.edu/catalog/ac:180566])

***** See Merriam: “continual use of off-beating without respite would cause a readjustment on the part of the listener, resulting in a loss of the total effect; thus off-beating [with respite] is a device whereby the listeners’ orientation to a basic rhythmic pulse is threatened but never quite destroyed” (Merriam, Alan P. “Characteristics of African Music.” Journal of the International Folk Music Council 11 (1959): 13–19.)

ALSO, I use the term “offbeatness” instead of ‘syncopation’ because the former is not norm-based, whereas the latter turns out to be so:

Coined by Toussaint as a mathematically measurable rhythmic quantity [1], offbeatness has proven invaluable to the preliminary work of understanding Afro-Brazilian (partido-alto) clave direction. It is interpreted here as a more precise term for rhythmic purposes than ‘syncopation’, which has a formal definition that is culturally rooted: Syncopation is the placement of accents on normally  unaccented notes, or the lack of accent on normally accented notes. It may be assumed that the norm in question is that of the genre, style or cultural/national origin of the music under consideration. However, in all usage around the world (except mine), normal accent placement is taken to be normal European accent placement [2, 3, 4].

For example, according to Kauffman [3, p. 394], syncopation “implies a deviation from the norm of regularly spaced accents or beats.” Various definitions by leading sources cited by Novotney also involve the concepts of “normal position” and “normally weak beat” [2, pp. 104, 108). Thus, syncopation is seen to be norm-referenced, whereas offbeatness is less contextual as it depends solely on the tactus.

Kerman, too, posits that syncopation involves “accents in a foreground rhythm away from their normal places in the background meter. This is called syncopation. For example, the accents in duple meter can be displaced so that the accents go on one two, one two, one two instead of the normal one two, one two” [4, p. 20; all emphasis in the original, as written]. Similarly, on p. 18, Kerman reinforces that “[t]he natural way to beat time is to alternate accented (“strong”) and unaccented (“weak”) beats in a simple pattern such as one two, one two, one two or one two three, one two three, one two three.” [4, p. 18]

Hence, placing a greater accent on the second rather than on the first quarter note of a bar may be sufficient to invoke the notion of syncopation. By this definition, the polka is syncopated, and since it is considered the epitome of “straight rhythm” to many performers of Afro-Brazilian music, syncopation clearly is not the correct term for what the concept of clave direction is concerned with. Offbeatness avoids all such cultural referencing because it is defined solely with respect to a pulse, regardless of cultural norms. (Granted, what a pulse is may also be culturally defined, but there is a point at which caveat upon caveat becomes counterproductive.)

Furthermore, in jazz, samba, and reggae (to name just a few examples) this would not qualify as syncopation (in the sense of accents in abnormal or unusual places) because beats other than “the one” are regularly accented in those genres as a matter of course. In the case of folkloric samba, even the placement of accents on the second eighth note, therefore, is not syncopation because at certain places in the rhythmic cycle, that is the normal—expected—pattern of accents for samba, part of the definition of the style. Hence, it does not constitute syncopation if we are to accept the definition of the term as used and cited by Kauffman, Kerman, and Novotney. In other words, “syncopation” is not necessarily the correct term for the phenomenon of accents off the downbeat when it comes to non-European music.

Moreover, in Meter in Music, Hule observes that “[a]ccent, defined as dynamic stress by seventeenth- and eighteenth-century writers, was one of the means of enhancing the perception of meter, but it became predominant only in the last half of the eighteenth century [emphasis added]. The idea that the measure is a pattern of accents is so widely held today that it is difficult to imagine that notation that looks modern does not have regular accentual patterns. Quite a number of serious scholarly studies of this music [European art music of 1600–1800] make this assumption almost unconsciously by translating the (sometimes difficult) early descriptions of meter into equivalent descriptions of the modern accentual measure” [5, p. viii] Thus, it turns out that the current view of rhythm and meter is not natural, or even traditional, let alone global. In fact, in Essential Dictionary of MUSIC NOTATION: The most practical and concise source for music notation is perfect for all musicians—amateur to professional (the actual book title) states that “the preferred/recommended beaming for the 9/8 compound meter is given as three groups of three eighth notes” [6, p. 73]. This goes against the accent pattern implied by the 9/8 meter in Turkish (and other Balkan) music, which is executed as 4+5, 5+4, 2+2+2+3, etc., but rarely 3+3+3. The 9/8 is one of the most common and typical meters in Turkish music, not an atypical curiosity. This passage is included here to demonstrate the dangers in applying western European norms to other musics (as indicated by the phrase “perfect for all musicians”).

[1]    Toussaint, G., 2005. Mathematical Features for Recognizing Preference in Sub-Saharan African Traditional Rhythm Timelines. Lecture Notes in Computer Science 3686:18-27. Springer Berlin/Heidelberg, 2005.                                                                                                                                [2]    Novotney, E. D. “The 3-2 Relationship as the Foundation of Timelines in West African Musics,” University of Illinois at Urbana-Champaign (Ph.D. dissertation), Urbana-Champaign, Illinois, 1998.
[3]    Kauffman, R. 1980. African Rhythm: A Reassessment. Ethnomusicology 24 (3):393–415.
[4]    Kerman, J., LISTEN: Brief Edition, New York, NY: Worth Publishers, Inc., 1987, p. 20.
[5]    Hule, G., Meter in Music, 1600–1800: Performance, Perception, and Notation, Bloomington, IN: Indiana University Press, 1999.
[6]    Gerou, T., and Lusk, L., Essential Dictionary of MUSIC NOTATION: The most practical and concise source for music notation is perfect for all musicians—amateur to professional, Van Nuys, CA: Alfred Publishing Co., Inc., 1996.