Gammachirp filter banks applied in roust speaker recognition based on GMM-UBM classifier
Joint Authors
Source
The International Arab Journal of Information Technology
Issue
Vol. 17, Issue 2 (31 Mar. 2020), pp.170-177, 8 p.
Publisher
Zarqa University Deanship of Scientific Research
Publication Date
2020-03-31
Country of Publication
Jordan
No. of Pages
8
Main Subjects
Abstract EN
In this paper, authors propose an auditory feature extraction algorithm in order to improve the performance of the speaker recognition system in noisy environments.
In this auditory feature extraction algorithm, the Gammachirp filter bank is adapted to simulate the auditory model of human cochlea.
In addition, the following three techniques are applied: cube-root compression method, Relative Spectral Filtering Technique (RASTA), and Cepstral Mean and Variance Normalization algorithm (CMVN).Subsequently, based on the theory of Gaussian Mixes Model-Universal Background Model (GMM-UBM), the simulated experiment was conducted.
The experimental results implied that speaker recognition systems with the new auditory feature has better robustness and recognition performance compared to Mel-Frequency Cepstral Coefficients (MFCC), Relative Spectral-Perceptual Linear Predictive (RASTA-PLP),Cochlear Filter Cepstral Coefficients (CFCC) and gammatone Frequency Cepstral Coefficeints (GFCC).
American Psychological Association (APA)
Deng, Lei& Deng, Lei. 2020. Gammachirp filter banks applied in roust speaker recognition based on GMM-UBM classifier. The International Arab Journal of Information Technology،Vol. 17, no. 2, pp.170-177.
https://search.emarefa.net/detail/BIM-954590
Modern Language Association (MLA)
Deng, Lei& Deng, Lei. Gammachirp filter banks applied in roust speaker recognition based on GMM-UBM classifier. The International Arab Journal of Information Technology Vol. 17, no. 2 (Mar. 2020), pp.170-177.
https://search.emarefa.net/detail/BIM-954590
American Medical Association (AMA)
Deng, Lei& Deng, Lei. Gammachirp filter banks applied in roust speaker recognition based on GMM-UBM classifier. The International Arab Journal of Information Technology. 2020. Vol. 17, no. 2, pp.170-177.
https://search.emarefa.net/detail/BIM-954590
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 176-177
Record ID
BIM-954590