SCIS & ISIS
SCIS & ISIS 2010
セッションID: FR-E1-1
会議情報
Improved Speech Recognition Filtering for Emergency Applications
*Young Im ChoSung Soon Jang
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会議録・要旨集 フリー

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抄録
Generally, the mal factor for speech recognition is the background noise. As the noise is the main cause for decreasing the performance, the place or environment is very important in speech recognition. To improve the speech recognition performance in the real situations where various extraneous noises are abundant, a novel combination of FIR and Wiener filters is proposed and experimented. The FIR filter first selectively passes through the frequency range of human voice or speech, and then the Wiener filter filters out the extraneous noises. The combination resulted in improved accuracy and reduced processing time, enabling fast analysis and response in emergency situations.
著者関連情報
© 2010 Japan Society for Fuzzy Theory and Intelligent Informatics
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