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Content-based Music Similarity with Triplet Networks

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Document pages: 3 pages

Abstract: We explore the feasibility of using triplet neural networks to embed songsbased on content-based music similarity. Our network is trained using tripletsof songs such that two songs by the same artist are embedded closer to oneanother than to a third song by a different artist. We compare two models thatare trained using different ways of picking this third song: at random vs.based on shared genre labels. Our experiments are conducted using songs fromthe Free Music Archive and use standard audio features. The initial resultsshow that shallow Siamese networks can be used to embed music for a simpleartist retrieval task.

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