Publication: Comparison of feature extraction for accent dependent Thai speech recognition system
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Issued Date
2018
Resource Type
File Type
application/pdf
Other identifier(s)
2-s2.0-85057580394
Rights Holder(s)
Scopus
Bibliographic Citation
2018 IEEE 7th International Conference on Communications and Electronics, ICCE 2018. (2018), p.322-325
Suggested Citation
Tantisatirapong S., Prasoproek C., Phothisonothai M. Comparison of feature extraction for accent dependent Thai speech recognition system. 2018 IEEE 7th International Conference on Communications and Electronics, ICCE 2018. (2018), p.322-325. doi:10.1109/CCE.2018.8465705 Retrieved from: https://hdl.handle.net/20.500.14740/5844
Author(s)
Abstract
This paper aims to compare the feature extraction methods for accent dependent Thai speech from three regions including central, southern and northeastern regions. We investigate four frequency analysis methods: i.e., Energy Spectral Density (ESD), Power Spectral Density (PSD), Mel-Frequency Cepstral Coefficients (MFCC) and Spectrogram (SPT). Radial basis function kernel based on support vector machine is used as a classifier with 5-fold cross validation. The isolated speech data sets are recorded from 30 male and 30 female participants speaking the 10 Thai digits from 0 to 9. The MFCC-based feature gives better accuracy than ESD, PSD and SPT respectively. For within the same region, the MFCC-based feature provides average accuracy of 94.9% and 99.1% for male and female voices respectively. For the three regions, the MFCC-based feature provides average accuracy of 89.34% and 93.81% for male and female voices, respectively. © 2018 IEEE.
Subject(s)
Electrostatic devices
Extraction
Power spectral density
Radial basis function networks
Spectral density
Spectrographs
Speech recognition
Support vector machines
Energy spectral density
Feature extraction methods
Mel frequency cepstral co-efficient
Mel frequency cepstral coefficients (MFCC)
Power spectral densities (PSD)
Radial basis function kernels
Spectrograms
Speech recognition systems
Feature extraction
Extraction
Power spectral density
Radial basis function networks
Spectral density
Spectrographs
Speech recognition
Support vector machines
Energy spectral density
Feature extraction methods
Mel frequency cepstral co-efficient
Mel frequency cepstral coefficients (MFCC)
Power spectral densities (PSD)
Radial basis function kernels
Spectrograms
Speech recognition systems
Feature extraction