PERSON IDENTIFICATION ALGORITHMS BY VOICE
Keywords:
speech signal, human identification by voice, feature set division, MFCC, GMM.Abstract
This paper discusses the use of the GMM method to build a human voice model for the task of human identification by voice. Voice recognition technology is available in a wide range of applications, including security, voice assistants, control systems, and more. The paper presents an approach based on the GMM method for modeling and classifying voice commands. The paper presents experiments on a set of audio data of the Karakalpak language. A comparative analysis of the LPC, LPCC, MFCC indicators was carried out in terms of identification accuracy and overall efficiency based on feature extraction algorithms.
References
H. Beigi. Fundamentals of speaker recognition. Springer US, 2011.
W. M. Campbell, D. E. Sturim, D. A. Reynolds, Support vector machines using GMM supervectors for speaker verification, IEEE signal processing letters 13 (5) (2006) 308–311.
Рабинер Л., Шафер Р. Цифровая обработка речевых сигналов. – М.: Радио и связ, 1981. – 496 с.
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.
П.Б.Нуримов, А.Н.Самижонов, Ш.И.Фозилов, З.М.Сулаймонов Шахсни нутқи асосида таниб олишда белгилар фазосини шакллантириш. Информатика ва энергетика муаммолари Ўзбекистон Журнали, №4, 2020
Desai D, Joshi M., Speaker Recognition Using MFCC and Hybrid Model of VQ and GMM. Recent Advances in Intelligent I nformatics 235: 53-63.
W. M. Campbell, D. E. Sturim, D. A. Reynolds, Support vector machines using GMM supervectors for speaker verification, IEEE signal processing letters 13 (5) (2006) 308–311.
Нуримов П.Б., Ережепов К.К., Шахсни овози бўйича биометрик таниб олиш тизимлари, Между-народной научно-практической конференции «Актуальные задачи математичес-кого моделирования и информа-ционных технологий» Nukus, May 2-3, 2023.
Fabian Pedregosa, Gaël Varoquaux, Alexandre Gramfort, ..., Scikit-learn: Machine Learning in Python,https://arxiv.org/abs/1201.04 90
James Lyons et al. (2020, January 14). jameslyons/ python_speech_ features: release v0.6.1 (Version 0.6.1).
Additional Files
Published
How to Cite
License
Copyright (c) 2024 Keulimjay Erejepov
This work is licensed under a Creative Commons Attribution 4.0 International License.
