Open Journal of Statistics

Volume 4, Issue 4 (June 2014)

ISSN Print: 2161-718X   ISSN Online: 2161-7198

Google-based Impact Factor: 1.45  Citations  

A Comparison of Classifiers in Performing Speaker Accent Recognition Using MFCCs

HTML  Download Download as PDF (Size: 2111KB)  PP. 258-266  
DOI: 10.4236/ojs.2014.44025    3,400 Downloads   5,387 Views  Citations

ABSTRACT

An algorithm involving Mel-Frequency Cepstral Coefficients (MFCCs) is provided to perform signal feature extraction for the task of speaker accent recognition. Then different classifiers are compared based on the MFCC feature. For each signal, the mean vector of MFCC matrix is used as an input vector for pattern recognition. A sample of 330 signals, containing 165 US voice and 165 non-US voice, is analyzed. By comparison, k-nearest neighbors yield the highest average test accuracy, after using a cross-validation of size 500, and least time being used in the computation.

Share and Cite:

Ma, Z. and Fokoué, E. (2014) A Comparison of Classifiers in Performing Speaker Accent Recognition Using MFCCs. Open Journal of Statistics, 4, 258-266. doi: 10.4236/ojs.2014.44025.

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