We've been working on this for a while. We're already recognizing music playing on hundreds of audio streams — in real-time, 24/7 — but before now, we provided the service only to clients with 10+ streams.
And now we've made music recognition for audio streams available to all of our users, for $45 per stream per month ($25 if you want your content to be recognized).
MusicBrainz is an open collaborative music database with metadata for tens of millions of songs.
We've integrated the MusicBrainz DB, so you can easily get all the information they have.
To access the MusicBrainz metadata, just send
musicbrainz in the return parameter.
Instagram, Twitter, TikTok, Facebook, OpenGraph, JSON-LD,
<audio> are supported.
Now you don't have to parse HTML pages. We've done this for you.We've integrated APIs of the social networks and a bit of code so you can send us URLs of the pages instead of doing a lot of parsing yourself and sending audio files.
Use it just like this: api.audd.io/?url=https://twitter.com/Vicetone/status/1247556387544035329.
Most of the Instagram, Twitter, TikTok and Facebook videos are supported; we also parse HTML for OpenGraph, JSON-LD media, and
We've created a status page so you always know if there are any issues with the API and if we already working on the resolving. We also hope to bring more transparency to how the issues are handled.
We’re launching Lis.tn: a new generation of song pages with links to all the music services.
Example of such a page: lis.tn/Warriors.
To create a page, just send an API request with
return=song_link, e.g. api.audd.io/?url=https://audd.tech/example1.mp3&return=song_link.
We’re launching our own really simple API dashboard right in our Telegram bot: t.me/auddbot?start=api.
Developers can now obtain an api_token, enjoy the trial period, and pay for one of our plans without leaving Telegram.
We're proud to be in top-12 Machine Learning APIs by ProgrammableWeb!
We've become official partners of Apple Music.
You can now use
apple_music instead of
itunes in the
return parameter and get more accurate and complete results than before.
+ Genre names (localized: if you send itunes_country=ru or market=ru, you'll get Russian words)
+ Composer names
+ Detailed information about the artwork (including text and background colors!)
+ Apple Music links
- iTunes track pricing
- iTunes links
P.S.: If you want to view beautiful JSON responses in your browser, we would recommend this extension
Now you can add
,spotify to the
return parameter to get Spotify metadata (including the album, song, artwork information, and links) about the recognized songs.
A month ago we built and tested real-time music recognition service for audio streams. Now we're ready to present it publicly.
The API is very simple: a client provides an URL for webhooks and then can add (by posting url and id of a stream), edit, delete or lists all the streams. Our server listens to the streams and sends webhooks with info about the songs being played (and about streams availability).
The service costs $45 per audio stream if you use our music DB containing 43 million songs or $25 per audio stream if you upload your own songs DB (you can provide just audios IDs, you don't have to send any titles, names or other metadata).
To use our music recognition services or to ask any questions, please contact [email protected]
If you need to send large (up to 1GB) audio files with a lot of songs inside, send us an email ([email protected]).
Also, enterprise clients can get ISRCs and UPCs.
Now we support asynchronous websocket requests.
Connect to wss://api.audd.io/ws/?api_token=[token] and send multiple requests (send files in binary form) without waiting for server's responses/results.
We have created a bot for Twitter.
🤖 recognizes music in videos, when someone mentions it in a tweet with a video or in reply to such a tweet.
Now our API recognizes music from audio tracks of video files (<32MB .mp4).
We have completely rewritten our services from PHP+Python to Golang and implemented a lot of cool things.
We've added the "all" parameter, that allows you to see all matched songs in audio files.
Usage example: YouTube Recognizer.
Also instead of sending
return=itunes_audios,deezer_audios,... or even
&return_itunes_audios=true&... you should simply send