I, I’m the author of the article and I already know that. The big difference between Roy van Rijn and I is that I only put algorithms whereas he put “ready to use” java code. On paper I should be bulletproof to any lawsuit since this article is nothing more than a very detailed version of the confounder Shazam paper (+some unexplained algorithms).

It's really unpleasant how they do not list the patents they think have been infringed. They just make a vague claim for everything, and realise that most people don't have the time, energy, nor money to challenge these broad claims in court and so most people just back down.

From its product - which is the users, who else?

it's likely Apple uses a custom-made version as well.

Siri uses Shazam to identify songs (as of iOS 8) [1]

[1] http://appleinsider.com/articles/14/09/19/siri-partners-with...

Apple definitely uses Shazam, because there's a Shazam icon next to the result: http://i.imgur.com/xTKUyyH.jpg

Have you ever noticed that the app has links where you can purchase the song that it found for you?

Here is one article about partnership with WMG:

http://www.billboard.com/biz/articles/news/digital-and-mobil...

There is a premium version of the app and they also have partnerships.

Think about the value of the data: they can predict trends long, long before anyone else can. After all, using Shazam almost equates to a "like". The music industry can figure out who likes what in practically realtime.

Exactly the article I was thinking of, and if you think of the way music is produced today, that's probably pretty useful and valuable data.

They seem to have a value add thing for TV adverts, I notice it a lot when I'm at my mum's and the TV is on. You see a pulsing shazam logo and presumably you shazam the advert and they redirect you to something from the advertiser. I assume they get paid there, maybe pretty well if they're really adding to the value of expensive TV ads.

It also works with SoundHound. Thanks for that, I didn't expect that song, that really made me laugh.

I have wanted to know how Shazam works for a long time. Thanks for this article man!

When I started this side project in 2012, I looked for publicly reliable information (especially thesis or research papers) and the only useful information I found was Shazam confounder’s paper.

Since this paper was written in 2003, I wouldn't be surprised if they have changed their algorithms since this time.

But from my understanding, the 2003 paper describes a highly scalable architecture and a noise tolerant and "time efficient" algorithm (that can be modified using thresholds) so it could still work in 2015 with a few optimizations. Still, I'm not working at Shazam and I'm not a researcher so I could be wrong.

Overly concise Matlab version. If you get Dan Ellis' ispecgram [1] you can do something like:

    [x, sr] = wavread('rick.wav');
    x_mono = mean(x,2);
    X = specgram(x_mono, nfft, sr);
    Y = X >= imdilate(X, ones(mask_size), 'same');
    y = ispecgram(Y, nfft, sr);
    % wavwrite(y, sr, 'roll.wav');

params: nfft, masksize (tuple)

[1] http://github.com/tbertinmahieux/MSongsDB/blob/master/Matlab...

This is a textbook example of fair use! A 5-second clip would have sufficed. it wouldn't have reproduced a large part of the work. it certainly wouldn't have affected the market for that work. it was for educational or criticism purposes, etc.

Just see the headings here:

https://en.wikipedia.org/wiki/Fair_use

OTOH I can see why the author would have wanted to steer a million miles of reproducing ANYTHING (including so much as mentioning the title of any work, which obviously isn't copyright infringement.)

in this case it's not so much copyright infringement as steering very very clear of reference to anything.

Fair use would seem to apply under most interpretations regardless (excerpts and quotations for the purposes of illustration are generally held to be covered), but you really can't say that for sure until the courts decide. There's nothing you can do to keep a rights holder from dragging you through court.

Nine Inch Nails released a couple albums under Creative Commons.

https://en.wikipedia.org/wiki/The_Slip_%28album%29

Never Gonna give You Up -- did I guess right?

Interesting how something can explain how something works without giving a hint as to what it does.

I really liked the way you put the article together, starting with the literal basics and working your way towards the solution. It's really inspiring to me, I tend to write articles that assume a lot of knowledge or gloss over the details of any basic research I've done, but seeing your article wants me to write up something similar for other concepts. Thank you!

https://pbs.twimg.com/media/BG4D5oOCUAEREoN.jpg

Yes, for a lot of stuff, especially for unit conversions and things like that.

Forgive the comment hijack, but for those interested in the basics of music information retrieval (MIR), I started to compile some notes on MIR as IPython notebooks here: http://musicinformationretrieval.com

It's clearly incomplete, but perhaps it might help someone. Pull requests are welcome.

I really like this kind of articles

Yeah this article got me confused because I had Monty in my head telling me different things then what I read here.

Agreed that signal processing can be a big topic. I thought it was well done to hit on the Nyqvist frequency to show why certain frequencies are used for sampling. Acoustics and audio processing are pretty good applications of some of this theory.

Nice article. I really wished every scientific paper would have such a nice explanation. (I still don't understand why e.g. Google scholar doesn't allow people to add their interpretation and questions and remarks etc. to any paper.)

I think this has been discussed a few times on HN. Here are some links. I know I'm missing 1 or 2 more:

https://news.ycombinator.com/item?id=1702975 https://news.ycombinator.com/item?id=909263

To a lesser extent: https://news.ycombinator.com/item?id=6683866

Not as detailed article, but if you are interested in this kind of things, here is how the audio fingerprinting algorithm used on AcoustID works:

https://oxygene.sk/2011/01/how-does-chromaprint-work/

The github links for this are missing though

Most of the libraries seem small and compact. Is there already one written in golang?

https://web.archive.org/web/20150713235721/http://coding-gee...