Automatic Live Music Song Identification Using Multi-level Deep Sequence Similarity Learning
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arXiv
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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866915103146770432 |
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| author | Hakala, Aapo Kincy, Trevor Virtanen, Tuomas |
| author_facet | Hakala, Aapo Kincy, Trevor Virtanen, Tuomas |
| contents | This paper studies the novel problem of automatic live music song identification, where the goal is, given a live recording of a song, to retrieve the corresponding studio version of the song from a music database. We propose a system based on similarity learning and a Siamese convolutional neural network-based model. The model uses cross-similarity matrices of multi-level deep sequences to measure musical similarity between different audio tracks. A manually collected custom live music dataset is used to test the performance of the system with live music. The results of the experiments show that the system is able to identify 87.4% of the given live music queries. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2501_08129 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Automatic Live Music Song Identification Using Multi-level Deep Sequence Similarity Learning Hakala, Aapo Kincy, Trevor Virtanen, Tuomas Audio and Speech Processing Sound This paper studies the novel problem of automatic live music song identification, where the goal is, given a live recording of a song, to retrieve the corresponding studio version of the song from a music database. We propose a system based on similarity learning and a Siamese convolutional neural network-based model. The model uses cross-similarity matrices of multi-level deep sequences to measure musical similarity between different audio tracks. A manually collected custom live music dataset is used to test the performance of the system with live music. The results of the experiments show that the system is able to identify 87.4% of the given live music queries. |
| title | Automatic Live Music Song Identification Using Multi-level Deep Sequence Similarity Learning |
| topic | Audio and Speech Processing Sound |
| url | https://arxiv.org/abs/2501.08129 |