Show HN: Discover what songs were used in YouTube videos

http://www.mooma.sh

by tk42 • 11 years ago

69 44 11 years ago

tk425• 11 years ago

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!

tomtoise• 11 years ago

Until you posted this clarification, my first thought was - What makes it different from Shazam?

Thanks for clearing that up, good luck with your site!

corobo• 11 years ago

Does it include music from oft-used music sources in YouTube videos such as AudioMicro and Incompetech[1]? I'd guess it's not really possible on the AudioMicro front as they're paid-for music that'd cost you a fortune to index but may be worth adding the latter

[1] http://incompetech.com/music/royalty-free/

unltd5• 11 years ago

I've worked on the echoprint-codegen algorithm for my current project ( trak.rocks ) and I'm curious about how you reimplemented the matching logic ?

Do you plan to document/opensource you work ?

mo05• 11 years ago

First we rewrote echonests truescore logic in perl and then altered slightly and implemented some extra checks to further try to exclude false positives. We also believe what they used in the late song/identify API might have been different from what is open sourced in https://github.com/echonest/echoprint-server

Also we pack each individual hash before storing in Elasticsearch and gained at least 50% storage space this way.

Our Fingerprint data is quite different from theirs(unreliable ID3 tags, N versions of same track) which is why we needed some tweaks. So far the matching is still far from perfect...

Whether we will open source the whole thing at some point we don't know yet.

samcrawford• 11 years ago

Do you have any intuition for whether the echhoprint-codegen algorithm would be suitable for saying whether two voice recordings match? One would be a little lossy, the other pretty much perfect.

lucaspiller• 11 years ago

Where do you get the MP3s from in the first place, and how long did it take to index 7 million?

mo05• 11 years ago

Crawling the internet for mp3s. It took us a couple of months to get to 7m.

GarethX• 11 years ago

It'd be good to have an option to provide an email address which results could be sent to once it has them, rather than keep checking an open tab.

mo05• 11 years ago

Good idea we'll keep it in mind. Bookmarking the ident page and coming back later to check on results will work too

unltd5• 11 years ago

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.

weavie• 11 years ago

Mix tapes is an ideal use case.

scrapcode• 11 years ago

One of the most common comments on YT videos I see are people asking for the name of the song used in a video.

pvaldes• 11 years ago

Yes, is one of the archetypical creatures of internet. I bet that 99% of those people are lawyers... or maybe the author of the song.

mo05• 11 years ago

Music used in compilations, ads, intros etc are typical usecases. Mixtapes & livesets of course are also great. But when pitch/bpms have been altered more than 1-2% we currently get a lot of false positives. We are still working on finding a solution to this.

unltd5• 11 years ago

I think I've read on the echonest board that the most common solution is to index multiple pitch variants of the same songs. Apparently that's what Shazam does.

Also the guys from Trax-air.com are doing something pretty similar to you guys but with pitch/bpm bending support.

p0l4rb34r• 11 years ago

I was thinking about this too but read before that the echonest fingerprinting doesn't handle pitch changes like Shazam.

Would be interested to know if you figured a way around that!

wingerlang2• 11 years ago

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

Hates_• 11 years ago

Does it still have to listen through a mic or can it detect songs from internal audio now? I don't have any speakers and just use headphones.

wingerlang2• 11 years ago

I don't really know. It's hard to test since I have only headphones with mics.

unltd5• 11 years ago

Shazam Mac osx app is quite powerful. It doesn't only listen to your mic so it will detect the song even when the sound is off. Also it often detects a song playing in somebody's else headphones at our office. Kinda creepy sometimes.

Kurtz79• 11 years ago

You can also use Siri on iOs 8 directly (it uses Shazaam as the backend service) .

http://www.cnet.com/how-to/siri-can-now-name-that-tune-via-i...

It works fairly well.

ToastyMallows• 11 years ago

You can also do this with Google Now

http://www.greenbot.com/article/2873722/how-to-perform-song-...

Again, works fairly well.

DanBC• 11 years ago

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.

kraymer• 11 years ago

have a look at beets <https://github.com/sampsyo/beets>, for the identification part it get its metadata from MusicBrainz/Discogs/filenames

IanCal• 11 years ago

Have you tried picard: https://picard.musicbrainz.org/

I used it to tag a massive amount of partially labelled and mostly metadata-free music files some time ago and it worked a treat.

vidyesh• 11 years ago

This is nice. Anything to tag TV Shows and Movies?

volker48• 11 years ago

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

mo05• 11 years ago

They display Audio info if tracks from the audioswap library were used: https://support.google.com/youtube/answer/94316?hl=en

huhtenberg• 11 years ago

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 :-/

tk425• 11 years ago

Hug of death occured faster than expected :) scaling now

amelius• 11 years ago

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).

mlinksva• 11 years ago

http://acousticbrainz.org/ ?

oxplot• 11 years ago

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?

DevFactor• 11 years ago

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.

Tunecrew• 11 years ago

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.

Show HN: Discover what songs were used in YouTube videos

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