Audio Feature Learning with Triplet-Based Embedding Network

No. 1: Thirty-First AAAI Conference On Artificial Intelligence

Volume

Proceedings of the AAAI Conference on Artificial Intelligence, 31

Student Abstract Track

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.

10.1609/aaai.v31i1.11071