Abstract
So far, few cover song identification systems aim at practical application. On one hand, existing sequence alignment methods achieve a high precision at the expense of high time cost. On the other hand, for large-scale identification, researchers attempt to exploit fixed low-dimensional features to reduce time cost. However, such highly compressed representations often result in a worse accuracy. In this paper, we propose an efficient two-layer system which takes advantage of the two kinds of methods. The proposed approach outperforms existing approaches and achieves high precision with relatively small time complexity.
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Acknowledgments
This work was supported by the Natural Science Foundation of China (No. 61370116).
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Xu, X., Cheng, Y., Chen, X., Yang, D. (2018). Efficient Two-Layer Model Towards Cover Song Identification. In: Schoeffmann, K., et al. MultiMedia Modeling. MMM 2018. Lecture Notes in Computer Science(), vol 10705. Springer, Cham. https://doi.org/10.1007/978-3-319-73600-6_11
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DOI: https://doi.org/10.1007/978-3-319-73600-6_11
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