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On Training Targets for Supervised Speech Separation
Formulation of speech separation as a supervised learning problem has shown considerable promise. In its simplest form, a supervised learning algorithm, typically a deep neural network, is trained to learn a mapping from noisy features to a time-frequency representation of the target of interest. Tr...
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| Publicat a: | IEEE/ACM Trans Audio Speech Lang Process |
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| Autors principals: | , , |
| Format: | Artigo |
| Idioma: | Inglês |
| Publicat: |
2014
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| Matèries: | |
| Accés en línia: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4293540/ https://ncbi.nlm.nih.gov/pubmed/25599083 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1109/TASLP.2014.2352935 |
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