PiCoGen: Generate Piano Covers with a Two-stage Approach
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arXiv
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| Auteurs principaux: | , , |
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| Format: | Preprint |
| Publié: |
2024
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| _version_ | 1866911972233052160 |
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| author | Tan, Chih-Pin Guan, Shuen-Huei Yang, Yi-Hsuan |
| author_facet | Tan, Chih-Pin Guan, Shuen-Huei Yang, Yi-Hsuan |
| contents | Cover song generation stands out as a popular way of music making in the music-creative community. In this study, we introduce Piano Cover Generation (PiCoGen), a two-stage approach for automatic cover song generation that transcribes the melody line and chord progression of a song given its audio recording, and then uses the resulting lead sheet as the condition to generate a piano cover in the symbolic domain. This approach is advantageous in that it does not required paired data of covers and their original songs for training. Compared to an existing approach that demands such paired data, our evaluation shows that PiCoGen demonstrates competitive or even superior performance across songs of different musical genres. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2407_20883 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | PiCoGen: Generate Piano Covers with a Two-stage Approach Tan, Chih-Pin Guan, Shuen-Huei Yang, Yi-Hsuan Sound Audio and Speech Processing Cover song generation stands out as a popular way of music making in the music-creative community. In this study, we introduce Piano Cover Generation (PiCoGen), a two-stage approach for automatic cover song generation that transcribes the melody line and chord progression of a song given its audio recording, and then uses the resulting lead sheet as the condition to generate a piano cover in the symbolic domain. This approach is advantageous in that it does not required paired data of covers and their original songs for training. Compared to an existing approach that demands such paired data, our evaluation shows that PiCoGen demonstrates competitive or even superior performance across songs of different musical genres. |
| title | PiCoGen: Generate Piano Covers with a Two-stage Approach |
| topic | Sound Audio and Speech Processing |
| url | https://arxiv.org/abs/2407.20883 |