EUROSPEECH 2001 Scandinavia
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.
Bibliographic reference. Martin, Arnaud / Damnati, Géraldine / Mauuary, Laurent (2001): "Robust speech/non-speech detection using LDA applied to MFCC for continuous speech recognition", In EUROSPEECH-2001, 885-888.