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.
| Mualliflar | Erejepov, Keulimjay |
|---|---|
| Jurnal | Al-Farg'oniy avlodlari |
| Nashr sanasi | 2024-12-26 |
| Son | 4 |
| Til | Rus |
речевой сигнал, идентификация человека по голосу, разделение набора признаков, MFCC, GMM, speech signal, human identification by voice, feature set division, MFCC, GMM., nutq signali, shaxsni ovozi orqali identifikatsiyalash, belgilar toʻplamini ajratish, MFCC, GMM.
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