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VSUGAN unify voice style based on spectrogram and generated adversarial networks
In course recording, the audio recorded in different pickups and environments can be clearly distinguished and cause style differences after splicing, which influences the quality of recorded courses. A common way to improve the above situation is to use voice style unification. In the present study...
| Autores principales: | , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Nature Publishing Group UK
2021
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8692613/ https://www.ncbi.nlm.nih.gov/pubmed/34934100 http://dx.doi.org/10.1038/s41598-021-03770-2 |