Show HN: Discover what songs were used in YouTube videos (opens in new tab)

The user can paste a youtube url which will then be analysed, fingerprinted and matched against a database of 7+ million audio fingerprints. It does not only identify a single song but is able to identify multiple songs contained in a single file or video and generates a timeline listing which tracks it contains at which time.

Our matching algorithm is based on the open source echoprint-codegen fingerprinting method, which we have built our own stack around:

- Replaced Solr/Tokyo Tyrant with Elasticsearch

- Reimplemented matching-logic

- Crawlers search multiple sources for audio files to be indexed (mp3s arent stored long term, only fingerprinted then deleted)

- Indexing about 1 new track per second

- Found method to verify unrealiable ID3 tags (in progress, current database also includes unferified)

- mogilefs as primary data store for fingerprints

- perl everything

We also provide a free music identification API.

Any feedback would be much appreciated!

Great Job !

Could you describe the usecases ? Is it for mixtapes uploaded on youtube by DJs, or Over-The-Air recognition in music festival videos ?

Because Music ( single tracks ) uploaded on youtube is usually already identified so it could be found.

For anyone often wondering about music in songs I will recommend Shazaams OSX app. It sits in the menu bar and listens to music and if it recognises something it will send a notification and add it to a list [0].

Watching youtube video, movies or just having someone else play something and it usually finds it without problems.

It's a different use case than OPs app though, which is more on demand I guess.

[0] http://i.imgur.com/0At4lJ6.png

I love this. Thank you.

On a slight tangent: I'd love a client that could identify my MP3 collection, and rename it and retag it (under some kind of supervision). Ideally it'd do the dentification in a batchmode when it got Internet connectivity (but this is perhaps an unreasonable requirement). And to make it perfect it would let me listen to and delete tracks.

I have a huge unweildy collection of MP3s and I can't bring myself to just delete gigabytes of music.

I think what we need most is a community-backed source of fingerprints. Because the authority-based approach only works well for popular songs (at least, that is my impression, based on frequently using commercial recognizing apps).

YouTube already does this on some videos does anyone know how this technique differs?

Tried with a couple of videos, went out to grab lunch and 30 minutes later it is still stuck (with the progress bar extending to the first t in "http://"). Sorry :-/

This is very interesting - I see this as an ideal concept to be paired with one of the existing commercial solutions, e.g. Shazam.

If you're indexing all the random and free stuff out there, you're picking up a lot of material that may have never been commercially released or has not been re-released digitally. At the same time, Shazam, YouTube ContentID, Apple's iTunes Match, etc. have access to an extremely large set of references which (more than you could have) contain 99% accurate metadata. ContentID definitely picks up multiple songs in mixes, as well as pitch changes, with a high degree of accuracy (assuming the master sound recording has been submitted to YouTube).

A submission system would be great too, or some way for persons to tag stuff themselves ala discogs, etc.

OK, I'm not if this occurred to anyone else: how about a Shazam like app that can search "the Internet" by listening a few seconds on your mic?

That's awesome. Now could you figure out why my intro #2 video: https://www.youtube.com/watch?v=dosy8zOooUU&list=PLP6PvXLevG...

Gets flagged as copyrighted music even though there is no music?

So many YouTuber's would thank you for a service that did this.