SPEAKER-DEPENDENT FEATURES FOR SPONTANEOUS SPEECH RECOGNITION
This paper presents the results of the study on improving robustness to the acoustic variability of the speech signal for spontaneous speech recognition system. The method is proposed to constructing high-level bottleneck features using deep neural network adapted to a speaker and to acoustic enviro...
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| Format: | Article |
| Language: | English |
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Saint Petersburg National Research University of Information Technologies, Mechanics and Optics (ITMO University)
2016-01-01
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| Series: | Naučno-tehničeskij Vestnik Informacionnyh Tehnologij, Mehaniki i Optiki |
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| Online Access: | http://ntv.ifmo.ru/file/article/14589.pdf |
| Summary: | This paper presents the results of the study on improving robustness to the acoustic variability of the speech signal for spontaneous speech recognition system. The method is proposed to constructing high-level bottleneck features using deep neural network adapted to a speaker and to acoustic environment with i-vectors. The proposed method provides 11,9% relative reduction of word error rate in Russian spontaneous telephone speech recognition task. |
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| ISSN: | 2226-1494 2500-0373 |