Preview

Информатика

Расширенный поиск

МЕТОД ОБЪЕДИНЕНИЯ РЕШЕНИЙ КЛАССИФИКАТОРОВ ДЛЯ ЗАДАЧИ РАСПОЗНАВАНИЯ ДИКТОРА

Аннотация

Предлагается использование нечетких интегралов для объединения решений классификаторов
систем распознавания диктора. В качестве набора признаков рассматриваются мгновенная частота и мгновенная амплитуда. Предлагаемый метод показывает значительно лучшие результаты по сравнению с применением единственного классификатора. Проводится сравнение предлагаемого метода с другими методами объединения решений классификаторов.

Об авторах

Я. Н. Имамвердиев
Институт информационных технологий Национальной академии наук Азербайджана
Россия


Л. В. Сухостат
Институт информационных технологий Национальной академии наук Азербайджана
Россия


Список литературы

1. Ross, A.A. Handbook of Multibiometrics / A.A. Ross, K. Nandakumar, A.K. Jain. – London : Springer, 2006. – 198 p.

2. Solomonoff, A. Advances in channel compensation for SVM speaker recognition / A. Solomonoff, W. Campbell, I. Boardman // Proc. of ICASSP. – Philadelphia, PA, 2005. – P. 629– 632.

3. Gader, P.D. Fusion of handwritten word classifiers / P.D. Gader, M.A. Mohamed, J.M. Keller //Pattern Recognition Letters. – 1996. – № 17. – P. 577–584.4. Michel, G. The representation of importance and interaction of features by fuzzy measure /G. Michel // Pattern Recognition Letters. – 1996. – № 17. – P. 567–575.

4. Kuncheva, L.I. Decision templates for multiple classifier fusion: an experimental comparison / L.I. Kuncheva, J.C. Bezdek, R.P.W. Duin // Pattern Recognition. – 2001. – № 34. – P. 299–314.

5. Mirhosseini, A.R. Human face image recognition: an evidence aggregation approach / A.R. Mirhosseini, H. Yan // Computer Vision and Image Understanding. – 1998. – № 71. – P. 213– 230.

6. Pham, T.D. Color image segmentation using fuzzy integral and mountain clustering / T.D. Pham, H. Yan // Fuzzy sets and systems. – 1999. – № 107. – P. 121–130.

7. Kwak, K.-C. Face recognition using fuzzy integral and wavelet decomposition method / K.- C. Kwak, W. Pedrycz // IEEE Transactions on Systems, Man, and Cybernetics. – 2004. – № 34. – P. 1666–1675.

8. Auephanwiriyakul, S. Generalized Choquet fuzzy integral fusion / S. Auephanwiriyakul, M.K. James, P.D. Gader // Information Fusion. – 2002. – № 3. – P. 69–85.

9. Wolf, J.J. Efficient acoustic parameters for speaker recognition / J.J. Wolf // J. Acoustical Society of America. – 1982. – Vol. 51, № 6. – P. 2044–2056.

10. Kinnunen, T. An overview of text-independent speaker recognition: from features to supervectors / T. Kinnunen, H. Li // Speech Communication. – 2010. – Vol. 52, № 1. – P. 12– 40.

11. Rose, P. Forensic speaker identification. Taylor & Francis forensic science series / P. Rose. N.Y. : Taylor & Francis, 2002. – 380 p.

12. Kinnunen, T. Spectral features for automatic text-independent speaker recognition. Licentiate thesis / T. Kinnunen. – Finland : University of Joensuu, 2003.

13. Маркел, Дж. Линейное предсказание речи / Дж. Маркел, А.X. Грей. – М. : Связь, 1980. – 308 с.

14. Furui, S. Cepstral analysis techniques for automatic speaker verification / S. Furui // IEEE tran. acoust., speech, signal processing. – 1981. – Vol. 27. – P. 254–272.

15. Reynolds, D. Channel robust speaker verification via feature mapping / D. Reynolds // Proc. of ICASSP. – Hong Kong, 2003. – Vol. 2. – P. 53–56.

16. Doddington, G. Speaker recognition based on idiolectal differences between speakers / G. Doddington // Proc. of Eurospeech. – Aalborg, Denmark, 2001. – Vol. 4. – P. 2521–2524.

17. Hemant, A.P. Forensic Speaker Recognition / A.P. Hemant, Amy Neustein. – Heidelberg : Springer, 2012. – 540 p.

18. Benediktsson, J.A. Consensus theoretic classification methods / J.A. Benediktsson, P.H. Swain // IEEE Trans. Systems Man Cybernet. – 1992. – № 22. – P. 688–704.

19. Ho, T.K. Decision combination in multiple classifier systems / T.K. Ho, J.J. Hull, S.N. Srihari // IEEE Trans. Pattern Anal. Machine Intelligence. – 1994. – № 16. – P. 66–75.

20. Xu, L. Methods of combining multiple classifiers and their applications to hand-written character recognition / L. Xu, A. Krzyzak, C.Y. Suen // IEEE Trans. Systems Man Cybernet. – 1992. – № 23. – P. 418–435.

21. Soong, F.K. On the use of instantaneous and transitional spectral information in speaker recognition / F.K. Soong, A.E. Rosenberg // IEEE Trans. Acoust. Speech, Signal Process. – 1988. – ASSP-36. – P. 871–879.

22. Farrell, K.R. Text-dependent speaker verification using data fusion / K.R. Farrell // IEEE Intern. Conf. on Acoustic, Speech and Signal Processing. – Detroit, Michigan, USA, 1995. – P. 349–352.

23. Sub-word speaker verification using data fusion methods / K.R. Farrell [et al.] // IEEE Workshop on Neural Networks for Signal Processing. – Amelia Island, Florida, 1997. – P. 531–540.

24. Farrell, K.R. An analysis of data fusion methods for speaker verification / K.R. Farrell, R.P. Ramachandran, R.J. Mammone // IEEE Intern. Conf. on Acoustic, Speech and Signal Processing. – Washington, USA, 1998. – P. 1129–1132.

25. Schalkwyk, J. Speaker verification with low storage requirements / J. Schalkwyk, N. Jain, E. Barnard // IEEE Intern. Conf. on Acoustic, Speech and Signal Processing. – Georgia, USA, 996. – P. 693–696.

26. Zadeh, L.A. Fuzzy sets / L.A. Zadeh // Information and Control. – 1965. – № 8. – P. 338– 353.

27. Gupta, M.M. Fuzzy measures and fuzzy integrals / M.M. Gupta, G.N. Saridis, B.R. Gaines. – N.Y. : Elsevier, 1977. – 510 p.29. Murofushi, T. A theory of fuzzy measures. Representation, the Choquet integral and null sets / T. Murofushi, M. Sugeno // J. Math. Anal. Appl. – 1991. – Vol. 159, № 2. – P. 532–549.

28. Maragos, P. On amplitude and frequency demodulation using energy operators / P. Maragos, J.F. Kaiser, T.F. Quatieri // IEEE Trans. on Signal Processing. – 1993. – Vol. 41, № 4. – P. 1532–1550.

29. Zhang, W.D. A priori threshold determination for phrase-prompted speaker verification / W.D. Zhang [et al.] // Proc. Eurospeech’99. – Budapest, Hungary, 1999. – P. 1203–1206.

30. Hamid, L.A. Quality based Speaker Verification Systems using Fuzzy Inference Fusion Scheme / L.A. Hamid, D.A. Ramli // Proc. of the Intern. Conf. on Communications, Signal Processing and Computers. – Interlaken, Switzerland, 2014. – P. 96–103.


Рецензия

Для цитирования:


Имамвердиев Я.Н., Сухостат Л.В. МЕТОД ОБЪЕДИНЕНИЯ РЕШЕНИЙ КЛАССИФИКАТОРОВ ДЛЯ ЗАДАЧИ РАСПОЗНАВАНИЯ ДИКТОРА. Информатика. 2015;(1):17-25.

For citation:


Imamverdiyev Y.N., Sukhostat L.V. MERGING CLASSIFIER DECISIONS FOR SPEAKER RECOGNITION. Informatics. 2015;(1):17-25. (In Russ.)

Просмотров: 704


Creative Commons License
Контент доступен под лицензией Creative Commons Attribution 4.0 License.


ISSN 1816-0301 (Print)
ISSN 2617-6963 (Online)