Research of speaker recognition based on combination of LPCC and MFCC

Spearker recognition used widely in our lives is an important branch of authenticating automatically a speaker's identity based on human biological feature. Linear Prediction Cepstrum Coefficient (LPCC) and Mel Frequency Cepstrum Coefficient (MFCC) are used as the features for text-independent...

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Bibliographic Details
Published in2010 IEEE International Conference on Intelligent Computing and Intelligent Systems Vol. 3; pp. 765 - 767
Main Authors Yuan Yujin, Zhao Peihua, Zhou Qun
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.10.2010
Subjects
DTW
Humans
LPCC
Mel frequency cepstral coefficient
MFCC
speaker recognition
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ISBN9781424465828
1424465826
DOI10.1109/ICICISYS.2010.5658337

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Summary:Spearker recognition used widely in our lives is an important branch of authenticating automatically a speaker's identity based on human biological feature. Linear Prediction Cepstrum Coefficient (LPCC) and Mel Frequency Cepstrum Coefficient (MFCC) are used as the features for text-independent speaker recognition in this system. And the experiments compare the recognition rate of LPCC, MFCC or the combination of LPCC and MFCC through using Vector Quantization (VQ) and Dynamic Time Warping (DTW) to recognize a speaker's identity. It proves that the combination of LPCC and MFCC has a higher recognition rate.
ISBN:9781424465828
1424465826
DOI:10.1109/ICICISYS.2010.5658337