Recognize Music
Identify music via line-in audio source or microphone with ACRCloud Music database.
Music Recognition Service enables your product ( apps or pc software ) to recognize music by sounds or files.
In this tutorial, we use the ACRCloud Music bucket, if you want to recognize your own content, please refer to Recognize Custom Content.
Sign up an account on this page and click the link on the verification email to complete the registration.
This only supports Audio Fingerprinting and Query by Humming, if you want to detect covers/live performances, please use File Scanning.
Go to your dashboard, build and configure an Audio & Video Recognition (AVR) project and attach the bucket named ACRCloud Music as below.
Choose Recorded Audio for the audio source to deal with noise.
Choose Line-in Audio for the audio source if you want to recognize files without noise.
Enable 3rd Party ID Integration if you need ISRC, UPC or IDs of Spotify, Deezer, Youtube etc.
Save the “host”, “access_key”, “access_secret” of your project for future use. You can find them in the places shown below.
Start sending requests with Mobile SDK, Backend SDK, Identification API or File Scan Tool. You can find all of the SDKs and Tools on this page.
For using our SDKs to scan files, SDKs will use 10 seconds of an audio clip for the recognition of a single request, you will need to send multiple requests to 1 file with different parts of the file if you want to get results from different parts of 1 file.
Basically you can manage everything you see above via the Console API below:
You will have 14 days for the free trial after registration. You can find the pricing on this page (login required), please make sure to check "ACRCloud Music bucket" and "3rd Party ID Integration" to get the full pricing.
Please feel free to add a credit card to upgrade to the paid customer to unlock more capacity if you are happy with our service.
Please refer to Branding Guidelines to place our brand on your products and contact us for up to 20% off discount!
You can detect covers/live performances on File Scanning with Audio/Video files or Youtube URLs
Go to "File Scanning" product and then go to "Containers" then click "Create" to create a container with ACRCloud Music bucket and other parameters.
Here are some explanations for the parameters:
Audio Engine:
Audio Fingerprinting: Only detect the exact same version.
Cover Song Identification: Detect covers/live performance.
Audio Fingerprinting & Cover Song Identification: Detect both options.
Audio Source:
Choose Recorded Audio for the audio source to deal with noise.
Choose Line-in Audio for the audio source if you want to recognize files without noise.
Scanning Policy:
Choose Traverse Scanning if you want to scan the entire file for multiple songs in different parts of the file.
Choose Points Scanning if there's only one song per file.
Go to the container you just created and click "Upload" to upload or add the files that you want to scan.
Data Type:
Audio: You can upload audio/video files;
Fingerprint: You can use the Audio File Fingerprinting Tool to generate fingerprint files and upload fingerprint files as they are much smaller (Cover Song Identification doesn't support fingerprint);
Youtube: You can simply input the Youtube video/channel/playlist URL if you want to detect Youtube video;
TikTok/Facebook/Instagram/Twitter: You can simply input the post URL if you want to detect video on those platforms;
When the "Status" turns "ready" you are able to click the arrow to browse the results on the page or select the files then click "Action" then click "Export" to export the reports.
You will have 14 days for the free trial after registration. You can find the pricing on this page (login required), please make sure to check "ACRCloud Music bucket" to get the full pricing.
Please feel free to add a credit card to upgrade to the paid customer to unlock more capacity if you are happy with our service.
Please refer to Branding Guidelines to place our brand on your products and contact us for up to 20% off discount!
Check out Music Metadata to get familiar with the JSON structure of the response data for future development.
Last modified 1yr ago