Déréverbération non-supervisée de la parole par modèle hybride
Fuente:
arXiv
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| Autori principali: | , , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| Soggetti: | |
| Accesso online: | |
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| _version_ | 1866915543544496128 |
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| author | Bahrman, Louis Fontaine, Mathieu Richard, Gaël |
| author_facet | Bahrman, Louis Fontaine, Mathieu Richard, Gaël |
| contents | This paper introduces a new training strategy to improve speech dereverberation systems in an unsupervised manner using only reverberant speech. Most existing algorithms rely on paired dry/reverberant data, which is difficult to obtain. Our approach uses limited acoustic information, like the reverberation time (RT60), to train a dereverberation system. Experimental results demonstrate that our method achieves more consistent performance across various objective metrics than the state-of-the-art. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2510_09025 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Déréverbération non-supervisée de la parole par modèle hybride Bahrman, Louis Fontaine, Mathieu Richard, Gaël Sound Artificial Intelligence Audio and Speech Processing This paper introduces a new training strategy to improve speech dereverberation systems in an unsupervised manner using only reverberant speech. Most existing algorithms rely on paired dry/reverberant data, which is difficult to obtain. Our approach uses limited acoustic information, like the reverberation time (RT60), to train a dereverberation system. Experimental results demonstrate that our method achieves more consistent performance across various objective metrics than the state-of-the-art. |
| title | Déréverbération non-supervisée de la parole par modèle hybride |
| topic | Sound Artificial Intelligence Audio and Speech Processing |
| url | https://arxiv.org/abs/2510.09025 |