Simulation and detection of tamil speech accent using modified mel frequency cepstral coefficient algorithm
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2018-06-08 https://doi.org/10.14419/ijet.v7i2.33.14202 -
Artificial Neural Network, Back Propagation Network, Mel Frequency Cepstral Coefficients, Speech Accent. -
Abstract
Automatic Speech reconstruction system is a topic of interest of many researchers. Since many online courses are come into the picture, so recent researchers are concentrating on speech accent recognition. Many works have been done in this field. In this paper speech accent recognition of Tamil speech from different zones of Tamilnadu is addressed. Hidden Markov Model (HMM) and Viterbi algorithms are very popularly used algorithms. Researchers have worked with Mel Frequency Cepstral Coefficients (MFCC) to identify speech as well as speech accent. In this paper speech accent features are identified by modified MFCC algorithm. The classification of features is done by back propagation algorithm.
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References
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How to Cite
Sarkar, S., R, S., S, R., & T J, H. (2018). Simulation and detection of tamil speech accent using modified mel frequency cepstral coefficient algorithm. International Journal of Engineering & Technology, 7(2.33), 426-428. https://doi.org/10.14419/ijet.v7i2.33.14202Received date: 2018-06-17
Accepted date: 2018-06-17
Published date: 2018-06-08