Experiments on the MFCC application in speaker recognition using Matlab

Kritagya Bhattarai, P. W.C. Prasad, Abeer Alsadoon, L. Pham, Amr Elchouemi

Research output: Book chapter/Published conference paperConference paper

11 Citations (Scopus)

Abstract

Speaker recognition is a very important research area where speech synthesis, and speech noise reduction are some of the major research areas. Speaker recognition is a new challenge for technologies. Many algorithms have been suggested and developed for feature extraction. This paper presents a feature extraction technique for speaker recognition using Mel Frequency Cepstral Coefficients (MFCC). Further, this paper evaluates experiments conducted along each step of the MFCC process. Finally, the paper compares hamming window and rectangular window technique based on the number of filters for accurate and efficient result in a Matlab environment. The result indicates that using a 32 filter with hamming window has more accuracy and efficiency compared to other windowing techniques and number of filters.
Original languageEnglish
Title of host publication7th International Conference on Information Science and Technology, ICIST 2017 - Proceedings
PublisherIEEE, Institute of Electrical and Electronics Engineers
Pages32-37
Number of pages6
ISBN (Electronic)9781509054015
DOIs
Publication statusPublished - 11 May 2017
Event7th International Conference on Information Science and Technology, ICIST 2017 - Da Nang, Viet Nam
Duration: 16 Apr 201719 Apr 2017
https://conference.cs.cityu.edu.hk/icist/ICIST2017_CFP.pdf

Conference

Conference7th International Conference on Information Science and Technology, ICIST 2017
CountryViet Nam
CityDa Nang
Period16/04/1719/04/17
Internet address

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