Abstract
Research on the ETSI speech enhancement system was conducted using traditional Wiener filter for noise reduction, which performed well when signal-noise ratio was high enough. However, when SNR decreased to a certain extent, it failed to suppress pulse noise effectively. Computational auditory scene analysis (CASA) simulating human auditory characteristics could make up for this weakness. Therefore, based on ETSI combined with CASA, a new speech enhancement algorithm was proposed, which performed feature extraction and spectrum estimation in the Gammatone domain rather than the original Mel domain as well as filtered out noise by an ideal ratio mask (IRM). On the noisy subset of the TIMIT corpus, the proposed enhancement achieves higher objective acoustic quality and proven ability to inhibit pulse noise under low SNR conditions compared to the original system. It also obtains an improvement in terms of the reduction of word error rates under low SNR conditions in the back-end speech recognition system.
Original language | English |
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Pages (from-to) | 663-669 |
Number of pages | 7 |
Journal | Tianjin Daxue Xuebao (Ziran Kexue yu Gongcheng Jishu Ban)/Journal of Tianjin University Science and Technology |
Volume | 48 |
Issue number | 8 |
DOIs | |
State | Published - Aug 15 2015 |
Bibliographical note
Publisher Copyright:©, 2015, Tianjin University. All right reserved.
Keywords
- Computational auditory scene analysis
- Gammatone filter
- Idea ratio mask
- Speech enhancement
ASJC Scopus subject areas
- General