A Novel Noise-Robust ASR Method by Applying Partially Connected DNN Model and Mixed-Bandwidth Concept
- 10.2991/3ca-13.2013.46How to use a DOI?
- robust; ASR; DNN; mixed-bandwidth
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.
- © 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 -