Robust speech/non-speech detection using LDA applied to MFCC for continuous speech recognition
نویسندگان
چکیده
Continuous speech recognition applications need precise detection because the number of words to recognize is unknown and vocabulary words can be short. The speech/non-speech detection must be robust to the boundary precision. In this work, a new approach to evaluate detection algorithm for continuous speech recognition is presented. The speech/non-speech detection using energy parameter combined with a Linear Discriminant Analysis (LDA) applied to Mel Frequency Cepstrum Coefficients (MFCC) is compared to the algorithm based on signal to noise ratio (SNR). The LDA applied to MFCC for speech/non-speech detection improves recognition performance in noisy environment and for continuous speech recognition applications.
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