Symbotunes: unified hub for symbolic music generative models
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arXiv
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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
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| _version_ | 1866917819214462976 |
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| author | Skierś, Paweł Łazarski, Maksymilian Kopeć, Michał Modrzejewski, Mateusz |
| author_facet | Skierś, Paweł Łazarski, Maksymilian Kopeć, Michał Modrzejewski, Mateusz |
| contents | Implementations of popular symbolic music generative models often differ significantly in terms of the libraries utilized and overall project structure. Therefore, directly comparing the methods or becoming acquainted with them may present challenges. To mitigate this issue we introduce Symbotunes, an open-source unified hub for symbolic music generative models. Symbotunes contains modern Python implementations of well-known methods for symbolic music generation, as well as a unified pipeline for generating and training. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2410_20515 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Symbotunes: unified hub for symbolic music generative models Skierś, Paweł Łazarski, Maksymilian Kopeć, Michał Modrzejewski, Mateusz Sound Artificial Intelligence Machine Learning Audio and Speech Processing Implementations of popular symbolic music generative models often differ significantly in terms of the libraries utilized and overall project structure. Therefore, directly comparing the methods or becoming acquainted with them may present challenges. To mitigate this issue we introduce Symbotunes, an open-source unified hub for symbolic music generative models. Symbotunes contains modern Python implementations of well-known methods for symbolic music generation, as well as a unified pipeline for generating and training. |
| title | Symbotunes: unified hub for symbolic music generative models |
| topic | Sound Artificial Intelligence Machine Learning Audio and Speech Processing |
| url | https://arxiv.org/abs/2410.20515 |