DocumentCode :
1653440
Title :
VOIP compressed-domain automatic speaker recognition based on probabilistic stochastic histogram
Author :
Dan, Qu ; Honggang, Yan ; Hui, Tang ; Bingxi, Wang
Author_Institution :
Zhengzhou Inf. Sci. & Techonology Inst., Zhengzhou
fYear :
2008
Firstpage :
692
Lastpage :
696
Abstract :
Compressed-domain automatic speaker recognition is based on the analysis of the compressed parameters of speech coders. This paper presents compressed-domain speaker recognition approach based on the Probabilistic Stochastic Histogram algorithm. We propose a framework based on Vector Quantization Probabilistic Stochastic Histogram(VQPSH) algorithm and perform speaker recognition on the feature vector which is directly extracted from G.729, G.723.1 6.3k, G723.1 5.3k compressed bit stream. We also propose a speaker recognition algorithm based on Gaussian Mixture Model Probabilistic Stochastic Histogram (GMMPSH). The experimental results show the Probabilistic Stochastic Histogram is superior to classical GMM using the same feature vector.
Keywords :
Gaussian processes; Internet telephony; probability; speaker recognition; vector quantisation; VOIP compressed-domain; automatic speaker recognition; gaussian mixture model; probabilistic stochastic histogram; speech coders; vector quantization; Automatic speech recognition; Decoding; Feature extraction; Histograms; IP networks; Internet telephony; Speaker recognition; Speech analysis; Stochastic processes; Vector quantization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signal Processing, 2008. ICSP 2008. 9th International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-2178-7
Electronic_ISBN :
978-1-4244-2179-4
Type :
conf
DOI :
10.1109/ICOSP.2008.4697225
Filename :
4697225
Link To Document :
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