2012 ©
             Publication
Journal Publication
Research Title Isarn Digit Speech Recognition using HMM 
Date of Distribution 15 January 2018 
Conference
     Title of the Conference The 2nd International Conference on Information Technology  
     Organiser Faculty of ICT,Mahidol University,Nakhon Pathom,Thailand 
     Conference Place Faculty of ICT,Mahidol University,Nakhon Pathom,Thailand 
     Province/State Nakhon Pathom 
     Conference Date 2 November 2017 
     To 3 November 2017 
Proceeding Paper
     Volume 2018 
     Issue
     Page 18-22 
     Editors/edition/publisher  
     Abstract Herein we present an automatic digit-speech recognition system for the Isarn language, which is a dialect spoken in the northeast of Thailand. In this work, an Isarn digit corpus was collected from natives speakers. The system utilizes the Mel Frequency Cepstral Coefficients (MFCC) technique to extract speech features, and the Hidden Markov Model (HMM) classifier for speech recognition. The paper focuses on isolated and continuous speech recognition for speakers (dependent and independent) uttering Isarn numerals (from 0 through 999). The system was evaluated by correctness. The results obtained from isolated recognition in speaker dependence and speaker independence were 90.00% and 79.80%, respectively; whereas continuous recognition provided results of 89.16% in speaker dependence and 82.47% in speaker dependence. 
Author
585020052-7 Miss SASITHRON SANGJAMRASCHAIKUN [Main Author]
Science Master's Degree

Peer Review Status มีผู้ประเมินอิสระ 
Level of Conference นานาชาติ 
Type of Proceeding Full paper 
Type of Presentation Oral 
Part of thesis true 
Presentation awarding false 
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