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Napster, Audio Fingerprinting, and the Future of P2P
mjmalone writes "Napster founder Sean Fanning is poised for a comeback, seems the now 22 year old Fanning has developed technology which creates "audio fingerprinting" of individual tracks and compares them against fingerprints in his firm's database to determine legality. A fee may be set and collected on a copyrighted track by its rightful owner. Fanning is actively recruiting industry support as well as pushing the idea to p2p services such as kazaa and grokster. " This isn't exactly new technology, but it's still interesting to see what Fanning is up to these days besides movie cameos.
You have to give him credit. At least someone out there is actually trying to make p2p legit, and not just throwing their weight around *cough* RIAA *cough*
if(md5sum("myfile.mp3") == md5sum("Limp_Bizkit-Crap.mp3")
cout "PIRATE!";
Will it be able to tell the diff between...
:)
Backstreet boys, N'Sync and other boy bands?
Creed, Nickleback and other "rock bands"?
50-cent and DMX?
I wonder if record companies will accept mistakes when differentiating between these artists
--
"I'm not bright. Big words confuse me. But Wanda loves me and that should be enough for you." - Cosmo
I recall that in its dying days Napster was talking about adding this to appease the recording industry. The variation then was from a company called Relatable. Sounds like Shawn is stuck in a recursive loop.
Umm no.
This is not going to make P2P "legit".
This is going to further destroy legit and non infringing usage of P2P. Now, RIAA will still say "p2p has no purpose other than piracy ban it"! And if people start paying for music from these services, guess what LEGITIMATE users of p2p suffer.
Sean Fanning did not invent P2P. Before napster we used to have IRC/DCC bots etc. and web search pages. Sean Fanning made downloading mp3's easier for the masses because of his windows client that automagically shared files you had downloaded. He's great but he's no God.
I remember seeing a book once that helped you identify songs by whether the sequence of notes at the beginning of the piece went up, down or stayed the same pitch when compared to the previous note. It was about the size of a telephone directory.
A quick Google finds out that its called The Parson's Code, with a lot more information here.
Presumably the fingerprinting scheme works in a similar fashion (over a larger portion of the song, and probably over multiple fragments of the song as well).
Ian.
A physicist is an atom's way of thinking about atoms
Such people don't "change sides" or comit "treason". They don't have any morales at all and work basically for any bloke who has money in his pockets. And Fanning thinks that this bloke is the music industry. I wonder, however, if they'll take him. Elephants are said to have good memory and to be unforgiving.
And for this P2P thing: does anyone here really think at the music industry will just lean back and watch their profits flush aways through DSL customer lines ?
Owner of a Mensa membership card.
Or P2P networks could NOT verify "legality," NOT pay Fanning anything, remain distributed enough to avoid any serious legal problems, shift the responsibility (rightfully) onto users, and music will remain -- as it was and ever shall be -- completely free.
Avast, me hearty! Arrrr!
before the "audio fingerprint" changes? Say, speed it up by 5%, filter out some of the bass and drum, and profit.
Karma: Food Fight (Mostly affected by Date Plate).
What if you introduced a little bit of static or something into the MP3? Not enough to be annoying, or maybe even really perceptible, but just enough to throw the "fingerprinting" off. I wonder if the technology is good enough to detect that. Also, if you were to record a song from vinyl, clean it up, and post it online, it might be different from the "official" version of the file. Maybe the technology might be able to detect the general pattern of the song, rather than exact sounds, but if not, Fanning's technology might not work out.
I produce electronic music and write little games. Have a look.
So you have a way of authenticating that a song is legitimately bought? An audit trail for each track? Wonderful. It's not going to be taken apart and cracked within a week is it? No-one's going to take our model and release a free implementation with much wider popular appeal are they? Are you sure? Great! We'll buy your company and give you generous stock options then.
...
Please excuse me now, my pet unicorn needs feeding
"It's not your information. It's information about you" - John Ford, Vice President, Equifax
He has a good business plan: create a big problem, then solve it.
I use the MusicBrainz tagger sometimes, and it works by comparing the audio signature of a song to the one in its database. This seems like the same sort of idea, but MusicBrainz tags files completly wrong a good percentage of the time, even listing the wrong artist - title info as a 100% match. I think this kind of technology has a ways to go before it could hold up in court or whatever.
"Sic Semper Tyrannosaurus Rex."
the cat's already out of the bag. The real issue here is the existence of the middleman in the music industry. Prices of CDs are artificially inflated by the middleman (the music outfits behind the RIAA), because they control most of the musical output in this country. Consumers want this music, and some continue to purchase at these inflated prices. But when you can get the same music, albeit illegal, from an alternate provider (KaZaA et al.), why bother paying those prices at all?
The solution is to bring the price of music back down to a reasonable level. If consumers are able to more directly compensate the artist for their music, and they can do so at a more granular level (i.e purchase tracks, vs CDs), and the easy of use is comparable to the p2p networks, then I bet you'll see a rebound in purchases. Granted, not all the people who use p2p will buy legit copies -- but I bet you'll see a significant rebound.
This country is long overdue for some overhauls on copyright / fair use law. The RIAA likens consumers who use p2p as criminals, but the RIAA backers have already been convicted for price fixing and routinely screw the artists they purport to represent out of cash. Criminals calling their target market criminals? Even if they're right, it's a matter of the pot calling the kettle black.
The days where the music industry could rob consumers without consequence is coming to an end. Exactly how it turns out is anybody's guess, but consumers are on to the RIAA's schemes and have a found a way to get their music without their shenanigans. Expect to see year-over-year sales to continue to fall until some of these leviathans go belly-up, and artists gain more control over production and licensing -- the way it should be.
The concept of audio "fingerprinting" is an interesting one, but likely outside of Fanning (and his local folks) experience or abilities. Fingerprinting has to rely on one of two things. The first is the artificialities of files -- things like file length, name, checksums, etc etc. All of these are easily overcome, and likely not robust to differing compression/bit rates/etc. The second thing it could reply on is data content -- that is, things like how many beats per minute, the time/frequency pattern in segment(s) X, Y, etc etc. I'll call this analysis of content. Unfortunately, simple analysis of content and watermarking schemes are very easily detected and overcome (remember the Felten/audio protection challenge?). TRUE analysis of content (when certain instruments play, their timing, the singing, etc) is a very difficult signal processing problem that won't be overcome without serious mathematics. And as much as I like Fanning, I don't think he's got the juice for it. Just my $0.02
MusicBrainz already has a free music fingerprint program. It identified about 60-70% of my songs correctly. It also will rename your files and update the ID tags.
The 30-40% it did not find... I could easily find by doing some searching manually through the program.
It was a nice way to completely identify my mp3 collection. Yes, it's a legal collection, but I wanted an easy way to rename the files and id tags.
Anyhoo... the program is pretty buggy so save often. Help the cause.
Enjoy.
DavaK
But audio fingering printing is very much a reality, and nobody uses a check sum.
There are many good papers on this.. I particularly like the one on "AudioDNA" visit your local google. You see with Audio Fingering Printing we are actually able to take a song that has been rerecorded onto an analog tape, slightly time stretched and still be able to tell that its the original song. It doesn't rely on bytes, but instead qualities of the audio signal.
There are many ways to do this, but one solid method is to analysis the audio signal for acoustic events that are resistant to change. Make a listing of these events and store there locations in time as a chain. Even if you only have a small segment of the chain you can search for it with techniques similar to the one's they use in biology (nobody looks for a complete DNA chain). Its a little difficult to explain without knowing something about signal processing so I suggest just searching the web. Here are a few good topics:
Music Information Retrival - (MIR)
Audio Finger Printing
Audio DNA
CUIDADO
ISMIR
MPEG-7
Oh and try not to insult all the people who research this stuff by claiming some goof at Napster invented it.
Rob
As a class project, a friend and I built a music recognition database. You can read our paper.
The general approach is fairly straightforward. You extract a set of "features" (typically several Mel Frequency Cepstral Coefficients, or MFCCs) from each sample of the song, say 10ms. You then pick several (say, 16) arbitrary points and iteratively generate that many "average" feature vectors, along with their weights so that they all sum to a one vector. This data is turned into a Hidden Markov Model (HMM). To see what audio you have, you run it through each of the possible HMMs and see which produces the greatest likelihood.
This method is typically applied to speaker recognition, where a linear search through HMMs is reasonable. This obviously isn't the case when you know about hundreds of thousands of songs, so a large part of the challenge is narrowing the field of HMMs to check (which is one of the focuses in our paper). Relatable, who were working with Napster a long time ago, have clusters that can classify 1,000 songs per second; I'm pretty sure they use this technique.
This technique has several important features. First, it doesn't depend on any properties of files themselves. Checksums would be trivial to beat, looking at a file's length could be circumvented by inserting silence, etc. Since this creates an average of sample data, a song would need to be changed quite a bit to fail to match. (The system is robust to, for instance, changes in bitrate, slowing the music down, and rearranging bits of the song or putting it in reverse.) We didn't have enough "derivative" music to test how it handles sampled music vs. the original -- it depends how much is changed.
Finally, this sort of system is useful for much more than song identification. You can build a model for an artist or genre and determine how to classify the song. One of my focuses in the paper is unsupervised genre classification -- my tests indicated some fairly reasonable groupings. This technique could be used for music recommendation -- "You like Dropkick Murphys? Well, they sound like Flogging Molly, so you might want to check them out."
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