Speaker Identification Using Discrete Wavelet Transform | Science Publications

Journal of Computer Science

Shanthini Pandiaraj¹  K. R. Shankar Kumar¹ 

关键词: Speaker Identification;    Discrete Wavelets;    Gaussian Mixture Model;   

DOI  :  10.3844/jcssp.2015.53.56

学科分类：计算机科学（综合）

来源: Science Publications

【 摘 要 】

This study presents an experimental evaluation of Discrete Wavelet Transforms for use in speaker identification. The features are tested using speech data provided by the CHAINS corpus. This system consists of two stages: Feature extraction stage and the identification stage. Parameters are extracted and used in a closed-set text-independent speaker identification task. In this study the signals are pre-processed and features are extracted using discrete wavelet transforms. The energy of the wavelet coefficients are used for training the Gaussian Mixture Model. Daubechies wavelets are used and the speech samples are analyzed using 8 levels of decomposition.

【 授权许可】

Unknown