There are many ways to ruin Christmas. Crappy gifts, drunken co-workers, eye-searing sweaters, family itself. (Hollywood makes a mint on the mini-genre of mirth-to-misery.)

But I’d like to go deeper than that. I’d like to attempt to scar your subconscious. I want to slice into that corner of your childhood memories that is still very fond of Christmas music. Sure, you say you hate these tunes now, that the infernal jingling-bells-makes-a-song-Christmassy trick makes you want to gore your ear with a flaming yule brand.

But you lie. And I would like to help you confront that lie, to eradicate the joy.

Back in the 1990′s, in the final supernova of cassette tape usage before its demise at the hands of digital, my pal ASG made me a unique holiday mix: the kristMess tape. Much of it is thick atonal drum-and-bass, but the nugget at the center is the gift beneath the bow. My gift. To you.

O Come All Ye Faithful, excerpt, 2:13

V/VM, The V/VM Christmas Pudding

Feel free to use this liberally throughout the next week as circumstances dictate. If Ebenezer and the Grinch aren’t cutting it for you and holiday horror doesn’t set you back on the right path, just put this on loop and relax. Halloween is only ten months away.

See also: Carbone Dolce

Lately I have been loving a few truly innovative audio apps for the iPhone, none having to do with it being an iPod.

I had always thought that mobile audio creation software were frivolous party tricks. Hey, look at me, I can play Baby Got Back on my 3″-wide keyboard! But that’s changed.

A while back I wrote about an idea for including audio processing code in the header of MP3 files. The premise was that, in addition to creating a music track, the artist would provide parameters for real-time playback modification based on user input, randomness, or anything else. The song would never (or at least wouldn’t ever have to) be the same.

The team at RJDJ have taken this idea to the extreme. The free and pay RJDJ apps in the iTunes store both provide “scenes”, akin to music tracks, complete with artwork. These scenes are nothing but audio processing algorithms.

All input happens via the lavalier microphone on the iTunes earbuds. Basically the scenes take the ambient noise surrounding you and remix it. Some of the scenes do this subtly, some are more musical, but all of them make you the focal point of the remix — not so much a musician as a conductor. I’ve listened to the noise of the L train, walking down the street, and the cacophony of three kids at dinner time. It is completely entrancing. Location-based remixing.

So, to our list of traditional musical interfaces — stick hitting animal skin, horse hair pulled across wire — we add one’s physical movement through life’s soundscape.

Here’s a more musical scene based on my eastward walk through the city a few days ago*. Note especially the interpolation of me almost being hit by a cab crossing Michigan Ave. at 1:16 (red marker on map). The horn makes the piece, in my opinion, but the beauty of this particular scene is how the bleeps and bloops are modulated by the ambient street noise.

View Larger Map

Of course this map isn’t connected in any way to playback control, but with the iPhone’s GPS it seems like an obvious evolution of the RJDJ app. The possibilities are many. How about a View in Google Maps button in iTunes? Or a site that aggregates user-created tracks and plots them over one another on a map, a personal-social musical-spatial mashup. Dan Hill’s city of sound, indeed.

——–

There are some other apps of note too.

Bloom is a generative music app from none other than Brian Eno, working with Brian Chilvers. You initiate notes of music by touching the screen. Each note plays and interacts with other notes in expanding concentric circles, like dropping pebbles in a pond. As with scenes in RJDJ, the parameters of note interaction are constrained by “moods”. These are the algorithms that govern the evolution of the sounds you start off. Spore for music. (Not a coincidence that Eno did the music for Spore, of course.)

Ocarina is one of those apps that makes you love the creators for thinking of it. Basically Ocarina turns your iPhone into a high-tech flute. OK, you say, I can see touching the screen like you cover the holes of a woodwind, but where do you blow? Why, the microphone of course! They’ve turned the lack of a wind guard on the iPhone mic into a feature! Light exhalation makes less noise on the mic and produces a lower intensity of the current note combination, and conversely. It’s brilliant really.

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* There’s no easy way to export audio from RJDJ, but this handy tool allows you to parse the backup file that the iPhone generates on your machine. You can pluck out the .wav files right from the RJDJ folder.

A while back my brother gave me several thousand songs from GoodBlimey.com. Almost all the tracks were mashups. Each song was composed of two songs by two different artists fairly equally smooshed together.

All the track titles were in the A vs. B format (e.g., Black Eyed Peas vs Kraftwerk) — and this gave me an idea.

I exported all the track data as a text file. Then my pal Chris Gansen wrote a script that nuked everything except the two artist names for each track and transformed the data into a spreadsheet like this:

A B 1
A C 1
B D 1
C D 3
C B 2
…

Then it was just a matter of plugging the data into ManyEyes and playing with the visualization types. The best by far is the bubble chart view. (Here’s the interactive chart.)Where the first two columns were artists names and the third column was the number of times they were mashed together in unique songs.

Each circle above represents a single artist. The larger the circle the more other artists the selected artist is mashed with.

The color slices actually tell you at a glance which other artists have been mashed … if you are an autistic savant who can pick out a single color in a sea of several hundred chromatic gradations, that is.

Much easier is clicking a circle which highlights the other artists with which it is mashed.

An alternate view gives the most complete information complete with number of mashed tracks per artist combination.

One other useful view was the network diagram. It shows actual connections between artist combos. The best feature of the diagram is that selected nodes highlight all the other artists with which it is matched. Easy to figure out who’s connected to whom. (Here’s the interactive diagram.)

So what have we learned? Certainly my data set does not contain every mashup ever made. But there were thousands and I think the charts give a good sense which artists mash best (look for the big circles) and mash best with whom.

But there’s far more that could be done. For one, there’s no data in these charts on which songs are being mashed. I have the info — just haven’t figured out how to integrate it. What I really would love to get at is why two artists make sense together. This would require stylistic data, notoriously subjective and consequently unreliable. Still, consider this but a start of the analysis.

Two particular projects influenced my work on this index. The History of Sampling by Jesse Kriss is a bar that I didn’t even come close to hitting, but it provided a great place to aim. And Andy Baio’s analysis of the samples in Girl Talk’s Feed The Animals showed what could be done with an idea, Amazon Turk, and some cool visualizations.

In truth, getting this data into shape was a massive pain in the ass. It was horribly formatted to begin with and took a great deal of kicking and shoving to play nicely with Many Eyes. Above all thanks to Chris — but Jesse Kriss, Frank Van Ham, and Martin Wattenberg of the Many Eyes team deserve applause too.

This is a lot cooler than My Music Genome, isn’t it?

So, iTunes Genius feature, it’s just you and me. Face-to-face. Gloves off. You think you know what I like? OK, you get one track to prove yourself.

No, no, that’s not fair. I’ll give you something really juicy to crunch on. How about you take a playlist that I described a while back as My Music Genome, the very seed (in my human algorithm-based estimation) of the majority of what I listen to now? Musical eugenics.

Oh, you don’t make playlists from other playlists? Only single tracks? Sucks. Fine, let me do this one-by-one. 12 tracks in the list; 25 recommendations per track. Let’s start being genius … Go!

Wait, what’s that? You can only identify 10 of 12 songs in my genome? You’re telling me that you have never heard of Orbital’s Impact or Vapourspace’s magnum opus? You have the Orbital track in your music store, for god’s sake!

OK, fine, go for it with the remaining 10. I’ll wait.

• Going Under – Devo
• The Robots – Kraftwerk
• This Wreckage – Gary Numan
• Squance – Plaid
• Halo – Depeche Mode
• Jericho – The Prodigy
• C/Pach – Autechre
• Stigmata – Ministry
• Aquarius - Boards of Canada
• Phantasm – Biosphere
• Gravitational Arch of 10 – Vapourspace
• Impact (The Earth Is Burning) – Orbital

Cool, 10 new playlists. Let me open them right up. 250 tracks. Subtract the “source” tracks, that gives me 240 songs that you think spring from my base musical tastes. Interesting.

——–

There are plenty of ways I could slice this data — Last.fm tags, AllMusic moods, BPM, waveforms — and I just might. But right now what jumps out at me are the duplicates. That is, the recommendations that come from two or more “source” songs from my genome. This might mean something.

The duplicates are important because they narrow the tree back down. They’re the inbred family members, points where multiple threads of interest converge. (In the image above, Hyped-Up Plus Tax by Dabrye, for instance, is a recommendation generated from both Plaid’s Squance and Kraftwerk’s The Robots.)

The overlaps are few, but meaningful.

• Aftermath – Tricky
• Children Talking – AFX
• Chime – Orbital
• The Curse of Ka’zar – Lemon Jelly
• Dominator [Joey Beltram Mix] – Human Resource
• A Forest [Tree Mix] – The Cure
• Future Proof – Massive Attack
• Gone Forever – Ulrich Schnauss
• Hyped-Up Plus Tax – Dabrye
• Laughable Butane Bob – AFX
• Little Fluffy Clouds – The Orb
• Me? I Disconnect From You – Gary Numan + Tubeway Army
• Mindphaser – Front Line Assembly
• Monkey Gone to Heaven – Pixies
• Paris – MSTRKRFT
• Satellite Anthem Icarus (apocryphal) – Boards of Canada
• Stars – Ulrich Schnauss
• We Are Glass – Gary Numan

A few identifiable strains emerge from this new “evolved” playlist. (These characteristics don’t necessarily reflect the dominant style of the artists themselves, just the tracks, which is more precise anyway.)

• shoe-gazy, downtempo: The Cure, Ulrich Schnauss, Boards of Canada, Dabrye
• hard-edged: AFX (aka Aphex Twin), Human Resource, Front Line Assembly, Pixies, MSTRKKRFT
• genre-benders: Tricky, Lemon Jelly, The Orb

(Not sure where Gary Numan fits in that typology, but he deserves to be in every list as far as I am concerned.)

Wow, John, that’s amazing, you’re thinking. You’ve managed to waste countless hours compiling data to tell yourself that you like soft music, hard music, and music that mixes the two. Such insight!

Actually it is interesting because the artists in this new playlist are some of my most-played. Lemon Jelly, Ulrich Schnauss, and Boards of Canada have been on heavy rotation for years. Clearly they are the fruit of stylistic seeds planted long ago. And now we have something approaching empirical proof. Truth is, most of what I listen to is either ambient or hard-edged or some outlying miscegenation. And there’s plenty of music that doesn’t fall into those categories.

The most interesting data point is that Satellite Anthem Icarus by Boards of Canada is the song that the iTunes Genius most thinks defines my music listening. It is part of multiple playlists generated from the source playlist.

Satellite Anthem Icarus – Boards of Canada

But here’s the crazy thing. That particular track is a fake. It is not the actual Boards of Canada track by the same name. It was included in a partially-bogus torrent download just prior to the official album being released. But I did actually fall in love with it. It is one of my favorite of their tracks. Except that it isn’t theirs. (Full story of this odd situation here.)

So, according to iTunes, the song that most represents the evolution of my musical taste is one that it should by all rights not even know about.

Now this gets to the heart of the mystery surrounding the Genius functionality itself. What exactly is it doing? It recommended this fake song to me which is neither named precisely what the real track is (in my library I have “(apocryphal)” in the title) nor is it the same length. And if by some crazy chance Apple is doing waveform analysis, it sounds nothing like the real version. So how could Genius recommend something that’s iTMS obviously doesn’t have in its library? Related, why would Genius not recognize the Orbital track in my library when I renamed it precisely as it is named in iTMS?

UPDATE: Commenter Pedro helpfully notes that this “fake” is actually Up the Coast by Freescha. Which makes this whole experiment really interesting. I agree with Apple that this song is extremely emblematic of my distilled music tastes, yet as noted above none of the metadata I had would have informed Apple to that. Is it possible that Apple is actually doing music analysis in the manner of Amazon’s text analysis? I really can’t believe that if for no other reason than that the initial Genius scan (when you run 8.0 for the first time) would take forever, which it did not. Still I want to believe. This is the way recommendations should happen.

I really don’t know how the recommendations are being generated, but I do think it is based on something more than store purchase data. Consider the jump from Ministry’s Stigmata to TMBG’s Ana Ng.

Stigmata – Ministry

Ana Ng – They Might Be Giants

There’s pretty much nothing similar between industrial music and irony-laden pop. But these two songs are definitely related when you consider their respective “hooks”: both use heavily-produced, effected, and clipped guitar noises as their main musical trope. Coincidence? Maybe, but why else would they be connected? Not music store data, methinks. Obviously Apple’s exact algorithm is a secret, but I’d love to know more.

——–

Some procedural notes. It helped that I already had a short playlist of stuff I considered influential. (Though I find it a lamentable shortcoming that Genius can’t generate a playlist from a playlist. It would have to infer commonality first then generate a new list. How tasty would that be?)

I then just set Genius to create a new playlist per track. Various recombinations of the playlists yielded a clean list which I flipped into a spreadsheet using the very handy Export Selected Song List AppleScript.

From the spreadsheet data I experimented with and aborted a bunch of different visualization ideas. At one point I had a monstrously large 10-headed Venn diagram in Illustrator that hurt to look at.

Eventually I created the network diagram in the screenshot at the top of this post using the wonderful Many Eyes social visualization site. (Yes, Many Eyes is IBM. Disclose that!)

A fuller, more interactive version of this visualization is available (Safari recommended, if you are on a Mac). Also the source data is there for the playing. I am sure there are other ways to massage it.

Enjoy this level of music nerdery? Dive into the Ascent Stage back catalog:

• The Mashability Index
• Aural decoration or, further adventures in filtering one’s music library
• Beyond shuffle
• Culinary turntablism

Today I stole an interesting link from Coudal about the removal of layers of ambient sound from a space as a kind of subtractive symphony.

Living in a house with three small children, I ponder silence as an abstraction, without empirical evidence. If nature abhors a vacuum, children abhor noiselessness. It’s instinctual, the reptile cortex responding to a threat of nothingness. Clear a space of quiet in my home and some child will yelp for no good reason. Like dangling meat in front of an animal that’s just eaten. It’ll still lunge.

But our response to silence is more complicated than that, of course.

Alex Ross, in his fantastic survey of 20th century classical music, The Rest Is Noise, explains Stravinsky’s innovation in syncopation (which is essentially putting silence where the rhythm suggests it shouldn’t be):

As the composer-critic Virgil Thomson once explained, the body tends to move up and down in syncopated or polyrhythmic music because it wants to emphasize the main beat that the stray accents threaten to wipe out. “A silent accent is the strongest of all accents,” he wrote. “It forces the body to replace it with a motion.” (Think of Bo Diddley’s “Bo Diddley,” with its “bomp ba-bomp bomp [oomph!] bomp bomp.”)

That concept makes a great deal of sense to me. The body physically desires to fill in the rhythmic gaps that music opens up. You may think you can only shake your booty to four-on-the-floor, but in fact silence, judiciously deployed, is just as effective at getting you going. In fact, more so: it’s cognitively unsettling to hear silence where a beat should be. Don’t just stand there, replace it with a motion!

And now, silence.

Humans share a common genome, so sayeth the biologists and the musicologists. But no one has the exact same genome. The various human genome cataloging projects compile an aggregate model, as does Pandora.

So, like the botanists stashing seeds in a vault in Norway in case of apocalypse, I present my own music genome — the albums that form the basis of my musical evolution.

There are other strands of nucleotides in my musical history, of course — Pink Floyd, The Smiths, They Might Be Giants come to mind — but the albums below have given rise to the most positive mutations. They aren’t my all time favorite albums or even the best in their own classes. But such is how one’s taste in music evolves.

Message to Future Scientists: If you are able to reconstruct me from fossilized genetic information please reprogram my musical knowledge according to the following list.

Gary Numan – Telekon
Kraftwerk – The Man-Machine
Devo – New Traditionalists
Ministry – The Land of Rape and Honey
Depeche Mode – Violator
The Prodigy – Experience
Orbital – Orbital 2
Vapourspace – Themes from Vapourspace
Biosphere – Substrata
Plaid – Double Figure
Autechre – Tri Repetae++
Boards of Canada – Music Has The Right To Children

And a mix I made, one track per album, just for you: My Music Genome.

So last night, mid-Zombiefest, my brother got a text message from a bar that he DJ’s at saying that the replacement DJ was awful: “He’s playing ‘let’s talk about sex, baby’ get over here now”. The bar manager needed an emergency DJ, stat.

We deliberated. Neither of us had anything set up for such a thing, we were in the midst of chronicling the undead, and had been drinking since 3pm. Oh, we were also wearing zombie masks. We didn’t deliberate long.

The DJ at the bar was none too pleased to be getting the hook. That’s what you get for playing George Michael to a bar full of twenty-somethings, buddy.

In our rush out of the house we forgot headphones. Let me suggest that this is a rather vital omission when attempting to play music. Cueing was, you know, impossible. It was all completely impromptu without a matched beat to be heard. But it was damn fun. Just back and forth musical one-upsmanship, echoes of Christmas Party.

In many ways a bar full of drunken patrons is not all that different from an assault of the living dead. Single-minded of purpose, responding only to the crudest instincts, lurching from prey to prey.* Yep, a Friday night bar scene.

The bar manager begged us not to put the zombie masks on. Inexplicably, we did not play Thriller.

The crowd was odd. The manager said they wanted 80′s and 90′s stuff. OK, can do. But every request that came in (none written on cocktail napkins, alas) was for hip hop, perhaps the most under-represented genre in my library. I mean, I have a good bit, but that’s not the point. I probably didn’t win the bar repeat customers by being a complete ass about music I didn’t want to play. Thankfully we had our pal Chris with us and after a while I just pointed to him as the designated request-taker when someone would approach. Shoulda been wearing this.

The bar wants us back tonight. The undead filmfest has resumed and we’re properly organizing tunes for the eve. I’m taking requests online only, so get yours in now.

* This is, in fact, the actual premise of Return of the Living Dead 5: Rave to the Grave, the inability to distinguish drug-addled revelers from brain-craving corpses. Tom Petty knows.

Had to get that egostroke of a post off the front, so here’s a fairly cool use — the first to my knowledge — of the EchoNest song analysis API that let’s you create custom beat-matched playlists just by pointing to tunes (or your Last.fm feed). Not at all perfect, but an interesting start. Here’s a quick one.

More fun at thisismyjam.com.

Many consider the Daft Punk headlining of Lollapalooza the most amazing arena rock show of 2007. But after tonight I gotta think Justice will one day claim the same title. Crazy Frenchmen. I’ve heard it called it the “French touch” but something’s in the water of Seine because these frogs can seriously rock out. It is 1970′s proto-headbanging in the electronic milieu. Just fantastic.

Here’s a concert-goer from the show. Looks like vector art, but he was human after all.