Unnayan Amitabh


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A Machine Learning based Music Retrieval and Recommendation System
Naziba Mostafa | Yan Wan | Unnayan Amitabh | Pascale Fung
Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)

In this paper, we present a music retrieval and recommendation system using machine learning techniques. We propose a query by humming system for music retrieval that uses deep neural networks for note transcription and a note-based retrieval system for retrieving the correct song from the database. We evaluate our query by humming system using the standard MIREX QBSH dataset. We also propose a similar artist recommendation system which recommends similar artists based on acoustic features of the artists’ music, online text descriptions of the artists and social media data. We use supervised machine learning techniques over all our features and compare our recommendation results to those produced by a popular similar artist recommendation website.