Proceedings of the IEEK Conference (대한전자공학회:학술대회논문집)
- 2004.08c
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- Pages.764-767
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- 2004
Telephone Speech Recognition with Data-Driven Selective Temporal Filtering based on Principal Component Analysis
- Jung Sun Gyun (School of Electronic and Electrical Engineering, Kyungpook National University) ;
- Son Jong Mok (School of Electronic and Electrical Engineering, Kyungpook National University) ;
- Bae Keun Sung (School of Electronic and Electrical Engineering, Kyungpook National University)
- Published : 2004.08.01
Abstract
The performance of a speech recognition system is generally degraded in telephone environment because of distortions caused by background noise and various channel characteristics. In this paper, data-driven temporal filters are investigated to improve the performance of a specific recognition task such as telephone speech. Three different temporal filtering methods are presented with recognition results for Korean connected-digit telephone speech. Filter coefficients are derived from the cepstral domain feature vectors using the principal component analysis.
Keywords
- Selective temporal filter;
- Principal component analysis;
- Telephone speech recognition;
- Feature extraction