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Show HN: Discover what songs were used in YouTube videos

mooma.sh

31–40 of 46 posts

Re: Show HN: Discover what songs were used in YouTube videos

#31
post #12
post #8

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.

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.

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.

Re: Show HN: Discover what songs were used in YouTube videos

#32
post #18

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://…

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.

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.

Re: Show HN: Discover what songs were used in YouTube videos

#33
post #21

Earlier quoted context omitted.

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 t…

When you say the matching is far from perfect, is that at your end or on the part of the echoprint / echonest code? You made tweaks because you found issues with what they were doing....?

The reason for it being far from perfect is likely a combination of both. If the correct song is indexed there is a high probabiliy for us to find the right match. However if its not, with a bit of bad luck a false positive can happen easily with the default solution (and ours too). Also when analysing a youtube video it can happen that in a 30sec snippet only 10 secs are a matching song and 20 are unrealated or 15 are one matching song the other 15 match a different one in which case 2 tracks or multiple versions of 2 different tracks will have relatively OK scores. Deciding what to consider a match (or whether to try different queries for the same or slightly altered timespan prior to deciding) is not trivial in these cases and our changes are mostly concerning when a match will be considered a match by altering thresholds and how matching truescores will be looked at in relation to other fingerprints true scores. Due to issues like these, specifying a timeframe for analysis will often produce better results.

http://static.echonest.com/echoprint_ismir.pdf

Re: Show HN: Discover what songs were used in YouTube videos

#34
post #5

Earlier quoted context omitted.

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 ?

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.

Echonest can work with voice but is optimized for music so you might encounter a lot of false positive with it. Check out the echonest board on google. It's a recurring topic.

Re: Show HN: Discover what songs were used in YouTube videos

#36
post #22
post #15

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 b…

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.

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

Re: Show HN: Discover what songs were used in YouTube videos

#37
post #17

Earlier quoted context omitted.

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

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

That's an absolutely creative way of doing it! Congrats. I'm interested in how you did it. For example, how do you exactly "crawl the internet"? Did you have a bunch of sites that you've pre-selected and then just crawl those or did you actually follow through on links?

Thanks.

Re: Show HN: Discover what songs were used in YouTube videos

#39
post #26

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).

http://acousticbrainz.org/ ?

Re: Show HN: Discover what songs were used in YouTube videos

#40
post #17

Earlier quoted context omitted.

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

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

I am also interested in knowing more specifics about your crawling process (if you can divulge).

Did you just crawl random sites and search for .mp3 content on them? Or did you have a set of pre-defined search sites to craw?

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