Audio Feature Learning with Triplet-Based Embedding Network
DOI:
https://doi.org/10.1609/aaai.v31i1.11071Keywords:
audio feature, metric learning, triplet networkAbstract
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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Published
2017-02-12
How to Cite
Qi, X., Yang, D., & Chen, X. (2017). Audio Feature Learning with Triplet-Based Embedding Network. Proceedings of the AAAI Conference on Artificial Intelligence, 31(1). https://doi.org/10.1609/aaai.v31i1.11071
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Student Abstract Track