Open Music Recommendation System (OpenMRS)

Personalized recommendation with deep learning.

About Acai

Acai is an open source project initialised by Berry Labs, a startup working towards machine learning algorithms to solve daily issues. Acai (codename) is trying to solve the problem of The Tyranny of Choice (a.k.a "Paradox of Choice) to describe the misery of users facing over-abundant choices. In the music area, especially in the age of streaming music, this paradox becomes so significant that it affects every single piece of choice when users try to enjoy music. It's why this project was born.
music notes gif

Why MRS?

Music recommendation engines are not new to the world. However, most of them are built on music catalog and acoustic fingerprints to generate playlist by similarities on genre, pattern etc. In addition to music data, some solutions leverage social media as well such as celebrities’ posts on Twitter. Adding social media information opens a new window of methodology of determining music preferences. But they are not neutral to the foundation of music appreciation, of which the most important element is the users themselves. The social effects resulted from the social media information lead to bias in music appreciation not only due to the limitation of exposure to music pools - most of the recommended tracks may come from selected lists like Billboard - but also potentially psychological effects such as peer pressure.

Why Open Source?

Acai OpenMRS uses a lot of open knowledge from researches and is built upon many successful concepts. We also test different open source building blocks in the community to evaluate those suitable for music recommendation. In return, we decide to make this project open source. In Berry Labs, we trust openness would generate more powerful and stable system, especially when a project is for tackling a super-scale problem. Every one, 100%, wouldn't reject music. It's why this issue is important to us, linking back to the human history and moving towards the future. We'd love to see how possible the further research and development can be vastly enhanced by collective expertise. While we keep investing in the major branches of OpenMRS, we trust there would be more interesting findings from the community and the hacking minds around the world.

Music listener?​

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Keep in touch

Hello ninja.

Glad you are still with us. Fork our GitHub repo and hack it!