The week's pick
Reseach Article
Comparative Study on the Performance of Mel-Frequency Cepstral Coefficients and Linear Prediction Cepstral Coefficients under different Speaker’s Conditions
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 90 - Number 11 |
| Year of Publication: 2014 |
| Authors: Kamil Ismaila Adeniyi, Oyeyiola Abdulhamid K. |
10.5120/15767-4460
|
Kamil Ismaila Adeniyi, Oyeyiola Abdulhamid K. . Comparative Study on the Performance of Mel-Frequency Cepstral Coefficients and Linear Prediction Cepstral Coefficients under different Speaker’s Conditions. International Journal of Computer Applications. 90, 11 ( March 2014), 38-42. DOI=10.5120/15767-4460
Abstract
This paper compares Mel-Frequency Cepstral Coefficients (MFCCs) and Linear Prediction Cepstral Coefficients (LPCCs) features under three speaker conditions: waking up, being fully awake and being tired, to determine which is better at handling the effect of these variations. A Gaussian Mixture Model (GMM) Classifier was used for both features. Experimental results show an identification rate of 83. 3% in the MFCC based system when the speakers were just waking up, while the LPCC based system had a lower identification rate of 75%. Also, when the speakers were either fully awake or tired, the MFCC based system achieved an identification rate of 100%, while the LPCC based system had an Identification rate of 91. 7%. In speaker verification, under the first condition (Waking Up), there is a significant difference between the equal error rates (EER), 7. 9% for MFCC and 22. 0% for LPCC. Also, there is a significant difference between the total success rates (TSR) under this condition. 82. 5% for MFCC and 65. 0% for LPCC. Overall, MFCC achieved a better total success rate under the three conditions studied.
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