SPEAKER MODELING BY PREPROCESSING SPEECH SIGNALS

Tashev K.A.; Fayzieva D.S.; Yuldasheva N.S.

doi:10.5281/zenodo.10031398

SPEAKER MODELING BY PREPROCESSING SPEECH SIGNALS

22.10.2023 International Scientific Journal "Science and Innovation". Series A. Volume 2 Issue 10

Tashev K.A., Fayzieva D.S., Yuldasheva N.S.

Abstract. This article examines the state of the art of speech activity boundaries, speech signal formation and processing technologies, and considers the attributes necessary for the speaker model.

Keywords: VAD algorithm, identification, verification, speaker model.

References:

1. H. Beigi. Fundamentals of speaker recognition. Springer US, 2011. 2. Amrouche, A. Effect of GSM speech coding on the performance of Speaker Recognition System / A. Amrouche, A. Krobba, M. Debyeche // 10th International Conference on Information Sciences Signal Processing and their Applications (ISSPA): Book of abstracts. - Kuala Eurnpur, 2010. - pp. 137-Nickel, R., “Automatic Speech Character Identification”, IEEE Circuits and Systems Magazine, vol. 6, no. 4, 2006, pp 8-29. 3. .Зилинберг А.Ю. Разработка и исследование временных и спектральных алгоритмов VAD (Voice Activity Detection) //А.Ю.Зилинберг, Ю.А.Корнеев //Российская школа-конференция «Мобильные системы передачи данных» / Зеленоград: МИЭТ, 2006. – С. 58–70. 4. Рабинер Л., Шафер Р. Цифровая обработка речевых сигналов. – М.: Радио и связь, 1981. – 496 с. 5. https://www.itu.int/rec/T-REC-G.729 6. Маматов Н.С., Нуримов П.Б., Самижонов А.Н. Нутқ сигналларида овоз фаоллигини аниқлаш алгоритмлари. «Ахборот коммуникация технологиялари ва дастурий таъминот яратишда инновацион ғоялар» Республика илмий-техник конференцияси 17-18 май 2021 йил. 7. X.-L. Zhang and J. Wu. Denoising deep neural networks based voice activity detection. In Acoustics, Speech and Signal Processing (ICASSP), 2013 IEEE International Conference on, pages 853–857. IEEE, 2013. 8. Hariharan M, Vijean V, Fook CY, Yaacob S. Speech stuttering assessment using sample entropy and Least Square Support vector machine. In: 8th International Colloquium on Signal Processing and its Applications (CSPA). 2012. pp. 240-245 9. Manjula GN, Kumar MS. Stuttered speech recognition for robotic control. Ahmad AM, Ismail S, Samaon DF. Recurrent neural network with backpropagation through time for speech recognition. In: IEEE International Symposium on Communica- tions and Information Technology (ISCIT 2004). Vol. 1. Sapporo, Japan: IEEE; 2004. pp. 98- 102 10. Shaneh M, Taheri A. Voice command recognition system based on MFCC and VQ algo- rithms. World academy of science. Engineering and Technology. 2009;57:534-538 11. Mosa GS, Ali AA. Arabic phoneme recognition using hierarchical neural fuzzy petri net and LPC feature extraction. Signal Processing: An International Journal (SPIJ). 2009;3(5): 161 12. Yousefian N, Analoui M. Using radial basis probabilistic neural network for speech recognition. In: Proceeding of 3rd International Conference on Information and Knowl- edge (IKT07), Mashhad, Iran. 2007 13. Cornaz C, Hunkeler U, Velisavljevic V. An Automatic Speaker Recognition System. Swit- zerland: Lausanne; 2003. Retrieved from: http://read.pudn.com/downloads60/sourcecode/ multimedia/audio/209082/asr_project.pdf 14. Shah SAA, ul Asar A, Shaukat SF. Neural network solution for secure interactive voice response. World Applied Sciences Journal. 2009;6(9):1264-1269 Some Commonly Used Speech Feature Extraction Algorithms http://dx.doi.org/10.5772/intechopen.80419 17 15. Ravikumar KM, Rajagopal R, Nagaraj HC. An approach for objective assessment of stuttered speech using MFCC features. ICGST International Journal on Digital Signal Processing, DSP. 2009;9(1):19-24 16. Kumar PP, Vardhan KSN, Krishna KSR. Performance evaluation of MLP for speech recognition in noisy environments using MFCC & wavelets. International Journal of Computer Science & Communication (IJCSC). 2010;1(2):41-45 17. Kumar R, Ranjan R, Singh SK, Kala R, Shukla A, Tiwari R. Multilingual speaker recogni- tion using neural network. In: Proceedings of the Frontiers of Research on Speech and Music, FRSM. 2009. pp. 1-8 18. Narang S, Gupta MD. Speech feature extraction techniques: A review. International Jour- nal of Computer Science and Mobile Computing. 2015;4(3):107-114 19. Козлов А.В. Система идентификации дикторов по голосу для конкурса NIST SRE 2013 // А.В.Козлов, О.Ю.Кудашев, Ю.Н.Матвеев, Т.С.Пеховский, К.К.Симончик, А.К.Шулипа // Труды СПИИРАН. – 2013. – № 2. – С. 350–370. 20. S. Furui. An overview of speaker recognition technology. In Automatic speech and speaker recognition, pages 31–56. Springer, 1996. 21. Макхоул Д. Векторное квантование при кодировании речи / Д.Макхоул, С.Рукос, Г.Гиш // ТИИЭР. – 1985. – Т.73. – №11. – С. 19–61.