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Hi,
I have fetched the "echoprintstring" with audio analysis API. so according to documentation, this echoprintstring is the fingerprint of the audio in EchoString format.
I'm building shazam like app. Now I want a way to create my own Echostring fingerprint or match given audio's fingerprint with the database of fingerprints so I can identify the song played with microphone. I tried searching in Echo Nest github account but I didn't find it there.
Help will be appreciated! thanks in advance.
The server that could do this is offline for years.
If it was possible, you weren't allowed to use Spotify data for your project according to the new Developer Terms and Policy.
The respons of the audio-analysis endpoint is huge, and you can only request these data one by one, so this would cause a huge load on the server of Spotify. That is also prohibited.
Hi Ximzend, thank you very much for your reply. what is your suggestion for building a shazam like application. Is there any alternative way through which I can make use of spotify API fingerprint data to identify music. If not, please suggest me some other alternative to build audio recognition app.
thanks in advance
There is no endpoint that you can use to search with a fingerprint. And as I said earlier, I don't recommend to download all the audio analysis data of Spotify for later use.
Here is a GitHub repo of someone who made a Shazam close: https://github.com/Lizzi-Busy/freezam
Correction of my first answer; I've found the repository to generate the Echoprint: https://github.com/spotify/echoprint-codegen
Some links in the repo are dead, so you'll need the following page for them: https://archive.org/web
HI Ximzend, thanks for your message. I tried running the repo but I'm facing some issues, tried sending Private message to you but its showing some error. Can you kindly share your contact details
I only found this repository, and did not run it myself. Also, I am not in reach of a computer for a couple of weeks, so I can't help you with it.
Here is a video on how Shazam: works https://youtu.be/b6xeOLjeKs0
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