Robust speech recognition by selecting mel-filter banks
- DOI
- 10.2991/eeeis-16.2017.52How to use a DOI?
- Keywords
- Speech recognition; Mel-filterbank (MFB); Melfilterbank energies; Mel-Frequency Cepstral Coefficients (MFCCs).
- Abstract
Mel-filterbank energies is a key feature that is widely employed in automatic speech recognition(ASR) system. It arises from a sub-band spectrum typically. But when the noise exists in the background, Mel-filterbank energies can not be easy to estimated accurately. In this paper, the fact that the trajectories of not only "traditional" log Mel-filterbank energies, but also its delta parameters can be influenced by noise will be theoretically analyzed. As a result, log Mel-filterbank energies and their delta parameters can not be calculated correctly. In this paper, we propose to remove those severely contaminated Mel-filterbank features and only keep those variations which perform better in the speech remained. We demonstrate the effectiveness of this novel operation through speech recognition experiments conducted on the Aurora-2 database.
- Copyright
- © 2017, 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 - Yun-Peng Wu AU - Jia-Min Mao AU - Wei-Feng Li PY - 2016/12 DA - 2016/12 TI - Robust speech recognition by selecting mel-filter banks BT - Proceedings of the 2nd Annual International Conference on Electronics, Electrical Engineering and Information Science (EEEIS 2016) PB - Atlantis Press SP - 407 EP - 416 SN - 2352-5401 UR - https://doi.org/10.2991/eeeis-16.2017.52 DO - 10.2991/eeeis-16.2017.52 ID - Wu2016/12 ER -