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A Machine Learning based Music Retrieval and Recommendation System

2016-05-01 · LREC 2016 5 · Naziba Mostafa, Yan Wan, Unnayan Amitabh, Pascale Fung

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.

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BIG-bench Machine LearningRetrieval

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