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The benefit of combining a deep neural network architecture with ideal ratio mask estimation in computational speech segregation to improve speech intelligibility
Computational speech segregation attempts to automatically separate speech from noise. This is challenging in conditions with interfering talkers and low signal-to-noise ratios. Recent approaches have adopted deep neural networks and successfully demonstrated speech intelligibility improvements. A s...
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| Wydane w: | PLoS One |
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| Główni autorzy: | , , , |
| Format: | Artigo |
| Język: | Inglês |
| Wydane: |
Public Library of Science
2018
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| Hasła przedmiotowe: | |
| Dostęp online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5953465/ https://ncbi.nlm.nih.gov/pubmed/29763459 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1371/journal.pone.0196924 |
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