Speech recognition based on lateral inhibition network auditory model

This paper studies the robust speech recognition based on auditory model. The spectrum of auditory representation shows that the lateral inhibition network (LIN) can shape the spatial input patterns and highlight their edges and peaks. Also, it can make the speech recognition to be more robust to noise than the LPC cepstral (LPC-CEP) approach. Some preliminary experiments including speaker dependent and speaker independent recognition were performed using both the model and LPC-CEP respectively. A set of 405 Chinese mandarin syllables was taken as the reference. The results of the experiment show that the recognition ratio based on the auditory model was equal to that of LPC-CEP in the case of non-noise. However, the recognition ratio based on the auditory model was much higher under the white noise of about 2.8 dB. Both theoretical and experimental studies show that the auditory model not only represents speech signal well but is also robust.