Comparing Front-End Enhancement Techniques and Multiconditioned Training for Robust Automatic Speech Recognition-Reference-Cited by-同舟云学术

Comparing Front-End Enhancement Techniques and Multiconditioned Training for Robust Automatic Speech Recognition

Published:2019 Issue: Volume: Page:329-340
ISSN:0302-9743
Container-title:Text, Speech, and Dialogue
language:
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Author:

Soni Meet H.,Joshi Sonal,Panda Ashish

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-030-27947-9_28

Reference30 articles.

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4. Das, B., Panda, A.: Robust front-end processing for speech recognition in noisy conditions. In: 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 5235–5239. IEEE (2017)

5. Dean, D.B., Sridharan, S., Vogt, R.J., Mason, M.W.: The QUT-NOISE-TIMIT corpus for the evaluation of voice activity detection algorithms. In: Proceedings of Interspeech 2010 (2010)

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