Proceedings of the 2nd International Symposium on Computer, Communication, Control and Automation

A Novel Noise-Robust ASR Method by Applying Partially Connected DNN Model and Mixed-Bandwidth Concept

Authors
Lichun Fan, Hongyan Li, Dengfeng Ke, Bo Xu
Corresponding Author
Lichun Fan
Available Online April 2013.
DOI
10.2991/3ca-13.2013.46How to use a DOI?
Keywords
robust; ASR; DNN; mixed-bandwidth
Abstract

In recent years, deep neural networks achieve significant improvements in automatic speech recognition. In this paper, we propose a deep structure used for robust ASR. The model has several partially connected layers which can suppress noise in different frequency bands. In order to recognize the speech data which has been distorted by noise seriously, we try to use parts of their frequency bands with a mixed-bandwidth model. The results have shown that the partially connected network could suppress noises in different frequency bands properly. The model's phone recognition on TIMIT corpus outperforms the state-of-the-art DNN model.

Copyright
© 2013, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2nd International Symposium on Computer, Communication, Control and Automation
Series
Advances in Intelligent Systems Research
Publication Date
April 2013
ISBN
978-90786-77-91-8
ISSN
1951-6851
DOI
10.2991/3ca-13.2013.46How to use a DOI?
Copyright
© 2013, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Lichun Fan
AU  - Hongyan Li
AU  - Dengfeng Ke
AU  - Bo Xu
PY  - 2013/04
DA  - 2013/04
TI  - A Novel Noise-Robust ASR Method by Applying Partially Connected DNN Model and Mixed-Bandwidth Concept
BT  - Proceedings of the 2nd International Symposium on Computer, Communication, Control and Automation
PB  - Atlantis Press
SP  - 182
EP  - 185
SN  - 1951-6851
UR  - https://doi.org/10.2991/3ca-13.2013.46
DO  - 10.2991/3ca-13.2013.46
ID  - Fan2013/04
ER  -