81–90 of 163 posts
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Some insight into the Shazam tech and article has a link to the algorithm being used. https://www.toptal.com/algorithms/shazam-it-music-processing...
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This has the smell of a comment written by someone with limited real-world experience. Simply writing down the list of problems you would have to solve to build Shazam would take an entire afternoon. Yes, deep neural networks have proven remarkably useful for machine perception, but you would still need to collect a colossal amount of audio data, fingerprint all of it, build a low-latency processing infrastructure fo…
> and convince a hundred million people to install your software to feed you copious real-world training data that you can use to improve model performance. That's actually the easy part. You already have the music. Distorting it by superimposing background noise is really not difficult.
I love Shazam but honestly, if they remove integrations like "Open in Spotify" which seems likely, I would probably switch to using SoundHound.
Apple is probably going to kill the app. They probably just bought it for the tech.
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This has the smell of a comment written by someone with limited real-world experience. Simply writing down the list of problems you would have to solve to build Shazam would take an entire afternoon. Yes, deep neural networks have proven remarkably useful for machine perception, but you would still need to collect a colossal amount of audio data, fingerprint all of it, build a low-latency processing infrastructure fo…
> and convince a hundred million people to install your software to feed you copious real-world training data that you can use to improve model performance. That's actually the easy part. You already have the music. Distorting it by superimposing background noise is really not difficult.
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This has the smell of a comment written by someone with limited real-world experience. Simply writing down the list of problems you would have to solve to build Shazam would take an entire afternoon. Yes, deep neural networks have proven remarkably useful for machine perception, but you would still need to collect a colossal amount of audio data, fingerprint all of it, build a low-latency processing infrastructure fo…
Shazam doesn't actually let you improve the answer, nor report incorrect guess. They are so confident with them, even if it's sometimes completely missed genre and style of music.
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It varies quite a bit from company to company. They were founded in 2001 so I expect most of it was salary and physical plant. The business is/was connecting resale opportunities to brands and artists[1] so you'll have a fairly significant sales and marketing effort although typically you will pay sales people for performance so their compensation will track revenue. But to give you some things to think about, if you…
For a company with offices in the most expensive cities in the world $120K is likely closer to the starting salary than the median.
Wow, that is an unusual exit after 6 rounds of funding. Crunchbase has it at $143M in funding up to that point. It goes to show how the switch from radio (station directed programming) to streaming (user directed programming) has put a huge crimp in music discovery and music promotion. [1] https://www.crunchbase.com/organization/shazam
Question from a non-Silicon Valley professional: Where does all that money go? Obviously, some [likely big] portion of it is still on the balance sheet, but does an app like Shazam really cost that much in engineering talent to update it and iterate it and server space to keep it running?
Salaries for - Chief Twitter Feed Monitor, Chief Assistant of The Twitter Feed monitor. The Special Secretary to The Assistant of Twitter Feed Monitor, etc etc etc
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You'd need access to the fingerprints database but otherwise should be fairly straightforward. What's not straightforward is recognizing cover songs and the like. But that's not only non-trivial but AFAIK can't be done.
> What's not straightforward is recognizing cover songs and the like. But that's not only non-trivial but AFAIK can't be done. Well, you could translate the music into actual notes (or musical intervals), and use Smith-Waterman (or any more advanced and more recent technique) to find the song with the lowest edit-distance.