Geodesic
Fuzzy model in the problem of the speaker identification by voice
Nečetkie sistemy i mâgkie vyčisleniâ, Tome 13 (2018) no. 1, pp. 37-43 Cet article a éte moissonné depuis la source Math-Net.Ru

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The article presents the speaker identification system developed on the basis of fuzzy model. The article provides the structure of a fuzzy model for solving the problem of voice identification. The method of decision-making is proposed. This method bases on the output data of the fuzzy system. Data are given about the results of identification for real speech base.
Keywords: biometric identification, text-independent speaker identification, speaker recognition, fuzzy sets, fuzzy model. 
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     author = {T. I. Antipina},
     title = {Fuzzy model in the problem of the speaker identification by voice},
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     url = {http://geodesic.mathdoc.fr/item/FSSC_2018_13_1_a2/}
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T. I. Antipina. Fuzzy model in the problem of the speaker identification by voice. Nečetkie sistemy i mâgkie vyčisleniâ, Tome 13 (2018) no. 1, pp. 37-43. http://geodesic.mathdoc.fr/item/FSSC_2018_13_1_a2/

[1] Osovskij S., Neural Networks for Information Processing, Finansy i Statistika Publ., Moscow, 2002, 287 pp. (in Russian)

[2] Rutkovskaya D., Pilin'skij M., Rutkovskij L., Neural Networks, Genetic Algorithms and Fuzzy Systems, Goryachaya Liniya Publ., Moscow, 2006, 452 pp. (in Russian)

[3] Al-Jawadi A. M. A., Speech Recognition and Retrieving using Fuzzy Logic System, Technical College, Foundation of Technical, Engineering, Mosul, Iraq, 2009

[4] Arthur D., Vassilvitskii S., “K-means++: the advantages of careful seeding”, Proceedings of the Eighteenth Annual ACM-SIAM Symposium on Discrete Algorithms, SODA 2007 (New Orleans, Louisiana, USA, January 7-9, 2007), 1027-1035

[5] Melin P., Urias J., Solano D., Soto M., Lopez M., Castillo O., “Voice recognition with neural networks, type-2 fuzzy logic and genetic algorithms”, Engineering Letters, 13:2 (2006), 108-116