Exploring Tokenization Methods for Multitrack Sheet Music Generation
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arXiv
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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866908100673404928 |
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| author | Wang, Yashan Wu, Shangda Du, Xingjian Sun, Maosong |
| author_facet | Wang, Yashan Wu, Shangda Du, Xingjian Sun, Maosong |
| contents | This study explores the tokenization of multitrack sheet music in ABC notation, introducing two methods--bar-stream and line-stream patching. We compare these methods against existing techniques, including bar patching, byte patching, and Byte Pair Encoding (BPE). In terms of both computational efficiency and the musicality of the generated compositions, experimental results show that bar-stream patching performs best overall compared to the others, which makes it a promising tokenization strategy for sheet music generation. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2410_17584 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Exploring Tokenization Methods for Multitrack Sheet Music Generation Wang, Yashan Wu, Shangda Du, Xingjian Sun, Maosong Sound Artificial Intelligence Audio and Speech Processing This study explores the tokenization of multitrack sheet music in ABC notation, introducing two methods--bar-stream and line-stream patching. We compare these methods against existing techniques, including bar patching, byte patching, and Byte Pair Encoding (BPE). In terms of both computational efficiency and the musicality of the generated compositions, experimental results show that bar-stream patching performs best overall compared to the others, which makes it a promising tokenization strategy for sheet music generation. |
| title | Exploring Tokenization Methods for Multitrack Sheet Music Generation |
| topic | Sound Artificial Intelligence Audio and Speech Processing |
| url | https://arxiv.org/abs/2410.17584 |