Spectrum warping based on sub-glottal resonances in speaker-independent speech recognition

In an effort to reduce the degradation caused by variation of different speaker in speech recognition,a new perceptual frequency warping based on sub-glottal resonances to speaker normalization is investigated.A new warping factor is extracted from the second sub-glottal resonance that is based on acoustic coupling between the sub-glottal and vocal tract.Second sub-glottal resonance is independent of the speech content,and it embodiment speaker character more than the third format.Then it is used to normalize the PMVDR coefficients,which are a speech coefficients based on perceptual Minimum variance distortionless response (PMDVR) and is more robustness and anti-noise than traditional MFCC,utilizing the normalized coefficients to speech mode training and recognition. The experiments show that the word error rate comparing with mel frequency cepstrum and the spectrum warping by third formant decreases 4% and 3% in clean speech recognition,9% and 5% in noise speech recognition.The results demonstrate this method to improve word recognition accuracy of speaker independent recognition system.