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Improving Robustness of Deep Neural Network Acoustic Models via Speech Separation and Joint Adaptive Training
Although deep neural network (DNN) acoustic models are known to be inherently noise robust, especially with matched training and testing data, the use of speech separation as a frontend and for deriving alternative feature representations has been shown to improve performance in challenging environm...
Gorde:
| Argitaratua izan da: | IEEE/ACM Trans Audio Speech Lang Process |
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| Egile Nagusiak: | , |
| Formatua: | Artigo |
| Hizkuntza: | Inglês |
| Argitaratua: |
2015
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| Gaiak: | |
| Sarrera elektronikoa: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4784988/ https://ncbi.nlm.nih.gov/pubmed/26973851 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1109/TASLP.2014.2372314 |
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