Open AccessSimulation and detection of tamil speech accent using modified mel frequency cepstral coefficient algorithm
Author(s) -
Swagata Sarkar,
R Sanjana,
S. Rajalakshmi,
T J Harini
Publication year - 2018
Publication title -
international journal of engineering and technology
Language(s) - English
Resource type - Journals
ISSN - 2227-524X
DOI - 10.14419/ijet.v7i2.33.14202
Subject(s) - mel frequency cepstrum , stress (linguistics) , speech recognition , tamil , hidden markov model , computer science , cepstrum , viterbi algorithm , artificial intelligence , field (mathematics) , pattern recognition (psychology) , feature extraction , mathematics , linguistics , philosophy , pure mathematics
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.