Author :
Suktangman, Nongnuch ; Khanthavivone, Kham ; Songwatana, Kraisin
Abstract :
This paper presents an optimization for vowel recognition in Thai spoken language. Thai language consists of 18 unmixed vowels (a,aa,i,ii,omega,omegaomega,u,uu,e,ee,epsi,epsiepsi,o,oo, gamma,gammagamma,sigmav,sigmavsigmav); and 6 mixed vowels (ua,u:a:,ia,i:a:,omegaa,omega:a:). Previously we have proposed use a 3-stage decision-making process: using voice energy and polynomial regression for short and long vowels classification; identifying voice segment (frame) into basic vowels; and using decision rule for recognition on unmixed and mixed vowels. The optimization is done by reducing the order of LPC and choosing a reduced set of critical band intensities (CBI). With this, the percentage accuracy remains high while processing time is decreased by 85%. The experiment is carried out on voice samples from 3 male model, 3 female model, and 2 male and 2 female model, yielding an accuracy of 91.47, 94.98, and 91.72 percents respectively
Keywords :
decision making; natural language processing; polynomials; regression analysis; speech recognition; Thai spoken language; critical band intensities; polynomial regression; reduced LPC spectrum; reduced feature set; three-stage decision-making process; voice energy; vowel recognition; Decision making; Equations; Humans; Linear predictive coding; Natural languages; Polynomials; Power engineering and energy; Speech analysis; Speech recognition; Transfer functions;
