Speech Recognition in Noisy Environment Using Different Feature Extraction Techniques
نویسندگان
چکیده
In this paper, different feature extraction methods for speech recognition system such as Melfrequency cepstral coefficients (MFCC), linear predictive coefficient cepstrum (LPCC) and Bark frequency cepstral coefficients (BFCC) are implemented and the comparison is done based on average recognition accuracy. We suggest a noise robust isolated word speech recognition system which can be applied in various noisy environments. In this method, Kalman filter is used to remove the background noise and to enhance the speech signal. The enhanced signal is integrated into the front end of recognition system in order to guarantee high performance in noisy environment conditions. Performance of different recognition methods are compared based on recognition accuracy rate in noisy environment.
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