The Music Bore – Video 2 from Nicholas Humfrey on Vimeo.

“I’m sorry, Dave, I can’t allow you to listen to Coldplay.”

What would radio be like if playlists were not only robotic, but had robot DJs pulling information from the Interwebs dynamically? That’s the question asked by the winning team at London’s Music Hackday last weekend, which created an epic mashup of data sources to produce a voice-synthesized IRC chatbot that researches and plays music for you.

Music Bore

Music Bore was just one of a number of projects developed in the weekend of musical hacking, some for listening, and at least one (a fantastic and free synth plug-in) for what we really like – production. With some of the world’s top musical coders in attendance, the results were amazing, even if not all projects were entirely finished. (Hey, that’s why they call it hacking.)

You can check out the full list on the wiki, but here are some favorites — and if you were there, do shout out to us as you put more documentation up of the event and projects.

Harmony Box by Dave and Mike is a synth plug-in for Mac (AU/VST) and Windows (VST, thus also Linux) that quickly creates lovely chords. I love the simplicity of the instrument – really lovely work, gents – and I think I may actually use it on a project. They accept donations if you’d like to see this instrument mature. Of course, with everyone else doing Web mash-ups, this didn’t win, but it’s more up our alley. (Web 2.0 – meh, whatever.)

The synth has its own project blog:
http://davenoise.com/blog/

Other winners (in our book, and as recommended by Harmony Box co-creator Dave Gamble):

LonelyHarps by Jamie Hollingworth and David Padbury is a Last.fm-based tool concept that helps you find dates – and choose the right tracks to set the mood – using music for compatibility. And, really, do you really want to date someone who doesn’t have musically compatible tastes? (I’m sure it’s just because they spotted lots of hotties on Last.fm, but…) The only bad news: the app didn’t actually get fully made yet, but we’ll stay tuned, gents. They do have impressive-looking formulas.

Music Zeitgeist by Cristiano Betta visualizes lyrics by decade, such as the 1980s, above. (Yeah, it was all about wanting and karma, the 80s.) Check out the project directly.

Theremag by Jono Cole and Jonty Wareing of Last.fm is actually the app I most want to see, but there’s no documentation yet. It’s a Theremin emulator on the Google Android-based HTC G1, with an unusual sensor — the built-in magnetometer (the one that normally acts as the compass) which was used to pitch-bend Michael Jackson. Once they get documentation up, expect to see it here. (I love that magnet sensor, too. Good fun.)

iPhone Music Visualizer by George J Cook and Matt Biddulph grabs Soundcloud files, analyzes them with Echonest (which recently got an iPhone-friendly Cocoa API), and then plays them back with a visualizer. It looks like a great place to get started if you’re planning on building something similar yourself.

In fact, it’s well worth checking out the wiki not only because some of the projects have (okay, sometimes-sloppy) source code, but point you at the resources you’d need to tackle something like this yourself if you’re a coder. And the event prompted a lot of folks from Last.fm to Echonest and BBC and others to get their APIs together.

It’s a terrific idea, and it sounds like we need another music hackday here. (Press releases, ahem, claimed this was the “first” music hackday, even though we’ve done a global event ourselves, but who cares — let’s do more!)

New York would make a nice base of operations for a similar event because a lot of folks with interesting APIs are here (or in nearby East Coast towns), but I think it’d be great to get more people online and not just in one locale.

What think you, sirs and madames? Tips on how we could make an online event work?

News may filter through Boing Boing, Slashdot, and Reddit – and certainly, this story already has. But oddly, I learned of this item when I happened to meet up with the blog item’s author in Somerville, Massachusetts. He has digital analysis he believes may prove that a track was recorded to a click track.

Paul Lamere is a developer at Echo Nest, a brainy think-tank of music geeks developing new ways of processing musical metadata in the cloud. Whereas services like Last.fm focus mainly on content and community, Echo Nest’s API wants to make the computers in the cloud smarter about how they listen to your music. We’ve had a look at their work twice before:

All Christmas Music, Boiled Down to Sixteen Droning Singles
Musical Brain API: An API for Music on the Web – And it Makes Pretty Pictures

The Remix API crunches data about rhythmic information at a number of levels. Since we first saw it, that API has led to an SDK (read: something you can program more directly), all assembled in Python. The Python-based SDK is now capable of creating the world’s most unlistenable mash-ups, among other things – some oddly compelling. On Friday, I got to listen to tunes with every other eighth note removed and Michael Jackson crossed with tunes – that is, until the programmers in the office started to complain because they were about to lose their mind. (Echo Nest uses a Sonos system to pipe music office-wide. I hope we can give you a preview of those clips soon.)

Remix SDK (currently Python)

But perhaps the most interesting thing this team has done so far is Paul’s work on plotting rhythmic analysis. Plots of tempo deviation, measured in beat durations, yield two interesting revelations:

In search of the click track [Music Machinery]

1. Much of the music you know has a lot of rhythmic variation. (Dizzy Miss Lizzie by the Beatles, anyone? No Ringo Starr jokes, please.)

2. A lot of the other music has disturbingly little rhythmic variation.

Yes, indeed, the use of click tracks (and, I suspect, metronomes, drum machines, quantized loops, and the whole lot) seems to be sucking some of the rhythmic spice out of music. You’ve already heard complaints about the “loudness wars” that have quantized out dynamic range. But, after decades of drum machines and digital tech, there’s surprisingly little complaint about quantized rhythmic values. Okay, perhaps I should scratch that – some people complain an awful lot. What we haven’t had until now is a visual representation of what’s going on.

Note/update: Just for the record, I’m not opposed to quantized beats. We’re very big fans of techno around here. The post Paul wrote begins, “Sometime in the last 10 or 20 years, rock drumming has changed.” Note, rock drumming. I think there are all sorts of rhythmic possibilities in different musical expressions.

I could go on, but I’m not having a very smart day. (The evening pot of coffee is on; I have high hopes.) Instead, I’m curious what people think of Paul’s methodology. This was just a programmer working along a line of thought with some experimental code, so I’m sure he doesn’t claim this to be an entirely scientific method. But that said, do you think his conclusions are correct? Is there more to be said about this subject?

For that matter, would there be a way to do more scientific work along these lines?

As for the engine that powered this: the Remix API and SDK from Echo Nest should be capable of quite a lot more, from gorgeous animated visualizations like the album art for Matmos we saw last year to unusual, new collaborative Web remix apps. The one catch is the analysis must be performed on their servers, so it’s not something you can apply without sending your content to the cloud – but you do get the metadata back, so I still think some sort of self-remixing applications might be possible, too. I’m eager to see a Java version of the SDK and not just Python, because that’d make it easier to add 3D elements or work with tools like Processing. Can I get an amen?

Well worth checking out Paul’s blog for lots of commentary on a variety of musical enthusiast topics:
Music Machinery