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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Pei Ding Lei He Xiang Yan Rui Zhao Jie Hao |
| Copyright Year | 2007 |
| Description | Author affiliation: Toshiba Res. & Dev. Center, Beijing, China (Pei Ding; Lei He; Xiang Yan; Rui Zhao; Jie Hao) |
| Abstract | This paper proposes a noise robust front-end with low computational cost for embedded in-car speech recognition. The minimum mean-square error (MMSE) estimation algorithm is adopted to suppress the background noise, and in the gain function calculation a suitable piece-wise linear function is used to substitute the traditional Taylor series accumulation method to simplify the computation complexity. After speech enhancement, spectrum smoothing is implemented in both time and frequency index with geometric sequence weights to further compensate the spectral components distorted by noise over-reduction. Experiments on Chinese isolated phrase recognition show that the proposed front-end significantly improves the recognition robustness in car environments while the computational load is extremely reduced. Compared with the ETSI advanced front-end, the average error reduction rate (ERR) of 12.2% and 4.5% is obtained in artificial car noisy speech and real in-car speech, respectively. |
| File Size | 5005911 |
| File Format | |
| ISBN | 1424407273 |
| ISSN | 15206149 |
| DOI | 10.1109/ICASSP.2007.367252 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2007-04-15 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Noise robustness Computational efficiency Speech recognition Working environment noise Estimation error Background noise Piecewise linear techniques Taylor series Speech enhancement Smoothing methods robustness speech recognition acoustic noise speech enhancement |
| Content Type | Text |
| Resource Type | Article |
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