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Deshun Yang

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2

IJCAI Conference 2019 Conference Paper

Temporal Pyramid Pooling Convolutional Neural Network for Cover Song Identification

  • Zhesong Yu
  • Xiaoshuo Xu
  • Xiaoou Chen
  • Deshun Yang

Cover song identification is an important problem in the field of Music Information Retrieval. Most existing methods rely on hand-crafted features and sequence alignment methods, and further breakthrough is hard to achieve. In this paper, Convolutional Neural Networks (CNNs) are used for representation learning toward this task. We show that they could be naturally adapted to deal with key transposition in cover songs. Additionally, Temporal Pyramid Pooling is utilized to extract information on different scales and transform songs with different lengths into fixed-dimensional representations. Furthermore, a training scheme is designed to enhance the robustness of our model. Extensive experiments demonstrate that combined with these techniques, our approach is robust against musical variations existing in cover songs and outperforms state-of-the-art methods on several datasets with low time complexity.

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AAAI Conference 2017 Short Paper

Audio Feature Learning with Triplet-Based Embedding Network

  • Xiaoyu Qi
  • Deshun Yang
  • Xiaoou Chen

We propose a triplet-based network for audio feature learning for version identiļ¬cation. 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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