Please use this identifier to cite or link to this item: https://ir.swu.ac.th/jspui/handle/123456789/12985
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dc.contributor.authorSueaseenak D.
dc.contributor.authorSangsai P.
dc.contributor.authorDetyong P.
dc.date.accessioned2021-04-05T03:21:58Z-
dc.date.available2021-04-05T03:21:58Z-
dc.date.issued2017
dc.identifier.other2-s2.0-85041894823
dc.identifier.urihttps://ir.swu.ac.th/jspui/handle/123456789/12985-
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85041894823&doi=10.1145%2f3168776.3168782&partnerID=40&md5=e45c0310f32c9076fb997352fd2e6854
dc.description.abstractThis paper presents the comparison study of the speech recognition system for the Thai language in the noise of the different environment. The well-known algorithms, such as MLP, SVM, GMM, HMM, VQ, DTW, DNN and End to End were used in this research. A test was conduced with 50 men and 50 women subjects during 5-60 years old. The proposed method consists of several parts which are (i) the feature extraction by Mel-frequency cepstral coefficients (MFCC) algorithm, (ii) The learning and decision process. The performance testing of the systems by the Ling's six sounds, such as ah, mm, oo, ee, sh and ss. The experiment results of our proposed method show that the accuracy of the system more than 80 percent. © 2017 Association for Computing Machinery.
dc.subjectBioinformatics
dc.subjectCharacter recognition
dc.subjectComparison study
dc.subjectDecision process
dc.subjectExercise training
dc.subjectMel-frequency cepstral coefficients
dc.subjectOptimal algorithm
dc.subjectPerformance testing
dc.subjectSpeech recognition systems
dc.subjectThai language
dc.subjectSpeech recognition
dc.titleThe optimal algorithm of sub-symptom threshold exercise training for aural habilitation/rehabilitation
dc.typeConference Paper
dc.rights.holderScopus
dc.identifier.bibliograpycitationACM International Conference Proceeding Series. (2017), p.48-51
dc.identifier.doi10.1145/3168776.3168782
Appears in Collections:Scopus 1983-2021

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