Multi-Task Autoencoder for Noise-Robust Speech Recognition

For speech recognition in noisy environments, we propose a multi-task autoencoder which estimates not only clean speech features but also noise features from noisy speech. We introduce the deSpeeching autoencoder, which excludes speech signals from noisy speech, and combine it with the conventional...

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Veröffentlicht in:	2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) S. 5599 - 5603
Hauptverfasser:	Zhang, Haoyi, Liu, Conggui, Inoue, Nakamasa, Shinoda, Koichi
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	IEEE 01.04.2018
Schlagworte:	Denoising autoencoder deSpeeching au-toencoder Ion radiation effects Magnetosphere Noise measurement Noise reduction robust speech recognition Speech recognition Task analysis Training
ISSN:	2379-190X
Online-Zugang:	Volltext
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