Speaker Recognition System using Wavelet Transform under Stress Condition

Kshirabdhi Tanaya Biswal, Janmejaya Rout


in this paper, we introduced a text-depend speaker recognition by using wavelet transform under stressed conditions. Here we compare different feature such as ARC, LAR, LPCC, MFCC, CEP and after comparison we found that LPCC provides best feature. For decompose signal at two levels Discrete Wavelet Transform is used here. Discrete Wavelet Transform (DWT) based Linear Predictive Cepstral Coefficients (LPCC) used as a feature for recognized the speaker system. For classification Vector Quantization method is used. Four different stressed data has selected for (SUSAS) i.e. stress speech data base for speaker recognition. Improvement is achieved 93% and 94% in case of Lombard and Neutral case.


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