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AAAI 2017

Audio Feature Learning with Triplet-Based Embedding Network

Short Paper Student Abstract Track Artificial Intelligence

Abstract

We propose a triplet-based network for audio feature learning for version identification. Existing methods use hand-crafted features for a music as a whole while we learn features by a triplet-based neural network on segment-level, focusing on the most similar parts between music versions. We conduct extensive experiments and demonstrate our merits.

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Context

Venue
AAAI Conference on Artificial Intelligence
Archive span
1980-2026
Indexed papers
28718
Paper id
415161728169142180