:: Music Recommendation Datasets ::.
One more dataset for MIR and Music Recommendation, compiled by Oscar Celma, and based around Last.fm data and APIs.
And some more detailed info here.
The guys at Echnest just realease their Echoprint – Open source music identification service. Looks really neat. There’s even an iOS app example here.
Last.FM also recently provided a audio fingerprinting API. More about this here.
So now it’s really simple to integrate audio fingerprinting in opensource apps. Looking forward to try it out soon.
An impressive feature data set extracted from music audio files by LabRosa using the Echonest API:
Million Song Dataset | scaling MIR research.
However, the feature set is (obviously) fixed and you have no access to the audio content of each music piece in the dataset (and there are some understandable reasons for that – check the FAQ). Nevertheless, a lot can already be done using this data (mainly for the machine learning, data mining, Information Retrieval folks), and this effort is a great contribution for the development of more advanced music recommendation systems.
Personally, I’m still very much into audio signal processing (mainly related to sound segregation, where I’m still trying to explore the basics of machine listening), so for now this dataset is not that useful to me…
Congratulations to LabRosa and Echonest for the effort and for making this public and available to the R&D community!
