Evaluation on data - Speaker dependability approaches for speech recognition tasks

In this feasibility study, four approaches in implementing speech recognition system for speech modeling are proposed. These approaches are based on data - speaker dependability of speech recognition system. Desired information or features in Mel Frequency Cepstral Coefficient (MFCC) are extracted f...

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Bibliographic Details
Published in2012 IEEE International Conference on Control System, Computing and Engineering pp. 254 - 258
Main Authors Saod, A. H. M., Sulaiman, S. N., Harron, N. A., Ahmad, A., Ramlan, S. A., Ramli, D. A.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.11.2012
Subjects
feature extraction
speaker dependent
speaker independent
speech disorder
speech recognition
Support Vector Machine (SVM)
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Summary:In this feasibility study, four approaches in implementing speech recognition system for speech modeling are proposed. These approaches are based on data - speaker dependability of speech recognition system. Desired information or features in Mel Frequency Cepstral Coefficient (MFCC) are extracted from the speech samples. For pattern matching, Support Vector Machine (SVM) classifier is used to perform the speech patterns classification. The main objective of this study is to evaluate the performance of data- speaker dependability approaches in term of percentage of accuracy and Mean Squared Error (MSE). Result suggests that data dependent - speaker dependent and data independent - speaker dependent approaches are more suitable to be used in speech recognition process as they both gave an accuracy of >95% and MSE <;0.2.
ISBN:9781467331425
1467331422
DOI:10.1109/ICCSCE.2012.6487151