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2014 Vol.33, Issue 1 Preview Page
31 January 2014. pp. 68-74
Abstract
References
1
1.B. Atal, “Effectiveness of linear prediction characteristics of the speech wave for automatic speaker identification and verification,” J. Acoust. Soc. Am. 55, 1304 (1974).
2
2.O. Viikki and K. Laurila, “Cepstral domain segmental feature vector normalization for noise robust speech recognition,” Speech Commun. 25, 133-147 (1998).
3
3.P. J. Moreno, B. Raj, and R. M. Stern, “A vector taylor series approach for environment-independent speech recognition,” in Proc. IEEE Int. Conf. Acoust. Speech Signal Proc. 2, 733-736 (1996).
4
4.N. S. Kim, “Statistical linear approximation for environment compensation,” IEEE Signal Proc. Lett. 5, 8-10 (1998).
5
5.R. C. Gonzalez and P. wintz, Digital Image Processing (Addision-Wesley Publishing Company, Reading, 1987), pp. 275-281.
6
6.J. C. Segura, C. Benitez, A. De La Torre, A. J. Rubio, and J. Ramirez, “Cepstral domain segmental nonlinear feature transformations for robust speech recognition,” IEEE Signal Proc. Lett. 11, 517-520 (2004).
7
7.A. de la Torre, A. M. Peinado, J. C. Segura, J. L. Perez-Cordoba, M. C. Benitez, and A. J. Rubio, “Histogram equalization of speech representation for robust speech recognition,” IEEE Trans. Speech Audio Proc. 13, 355-366 (2005).
8
8.J. Pelecanos and S. Sridharan, “Feature warping for robust speaker verification,” in Proc. Speaker Odyssey, 213-218 (2001).
9
9.M. Skosan and D. Mashao, “Modified segmental histogram equalization for robust speaker verification,” Pattern Recognit. Lett. 27, 479-486 (2006).
10
10.M. Skosan and D. Mashao, “Matching feature distributions for robust speaker verification,” in Proc. PRASA, 42-47 (2004).
11
11.R. O. Duda and P. E. Hart, D. G. Stork, Pattern Classification (John Wiley & Sons, New York, 2012), pp. 528-530.
12
12.D. A. Reynolds, T. F. Quatieri, and R. B. Dunn, “Speaker verification using adapted gaussian mixture models,” Digit. Signal Process. 10, 19-41 (2000).
13
13.M. Kim, I. Yang, and H. Yu, “Histogram Equalization Using Centroids of Fuzzy C-Means of Background Speakers’ Utterances for Speaker Identification,” in Proc. Stat. Lang. and Speech Proc. 1, 143-151 (2013).
14
14.I. Oh, Pattern Recognition, (in korean, Kyobobook, Seoul, 2008), pp. 438-441.
15
15.G.729 [online], http://www.itu.int/rec/T-REC-G.729-200701-S/en.
16
16.SILK [online], https://developer.skype.com/silk.
17
17.Speex [online], http://www.speex.org/.
Information
  • Publisher :The Acoustical Society of Korea
  • Publisher(Ko) :한국음향학회
  • Journal Title :The Journal of the Acoustical Society of Korea
  • Journal Title(Ko) :한국음향학회지
  • Volume : 33
  • No :1
  • Pages :68-74
  • Received Date : 2013-10-23
  • Accepted Date : 2013-11-22