DocumentCode :
2800036
Title :
N-gram nearest neighbor algorithm for voice password system
Author :
Guo, Wu ; Zhang, Zhao ; Long, Yanhua ; Dai, Lirong
Author_Institution :
MOE-Microsoft Key Lab. of Multimedia Comput. & Commun., Univ. of Sci. & Technol. of China (USTC), Hefei, China
fYear :
2010
fDate :
14-19 March 2010
Firstpage :
4438
Lastpage :
4441
Abstract :
A specific issue in the voice password system is addressed in this paper: When the text content of target speaker´s enrollment password has been already known by imposters, they can do a well-behaved impersonation using the same text content as the target speaker. This results in a much higher false acceptance than the traditional voice password system. N-gram based nearest neighbor algorithm is proposed here to improve the speaker detection accuracy. Furthermore, correlation coefficient is adopted as the distance measurement between two acoustic features instead of the traditional Euclidean distance. Experimental results show that the proposed method outperforms the DTW and GMM-UBM algorithms.
Keywords :
distance measurement; learning (artificial intelligence); security of data; speaker recognition; text analysis; Euclidean distance; N-gram nearest neighbor algorithm; acoustic feature; distance measurement; speaker detection; target speaker enrollment password; text content; voice password system; Acoustic signal detection; Books; Euclidean distance; Heuristic algorithms; Hidden Markov models; Loudspeakers; Nearest neighbor searches; Neural networks; Speaker recognition; Speech; dynamic time warping; nearest neighbor; speaker recognition;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics Speech and Signal Processing (ICASSP), 2010 IEEE International Conference on
Conference_Location :
Dallas, TX
ISSN :
1520-6149
Print_ISBN :
978-1-4244-4295-9
Electronic_ISBN :
1520-6149
Type :
conf
DOI :
10.1109/ICASSP.2010.5495621
Filename :
5495621
Link To Document :
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