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Using recurrent neural networks to improve the perception of speech in non-stationary noise by people with cochlear implants
Speech-in-noise perception is a major problem for users of cochlear implants (CIs), especially with non-stationary background noise. Noise-reduction algorithms have produced benefits but relied on a priori information about the target speaker and/or background noise. We developed a recurrent neural...
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| Publicado no: | J Acoust Soc Am |
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| Main Authors: | , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
2019
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6773603/ https://ncbi.nlm.nih.gov/pubmed/31370586 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1121/1.5119226 |
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