Publication:
The optimal algorithm of sub-symptom threshold exercise training for aural habilitation/rehabilitation

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Issued Date

2017

Resource Type

Conference Paper

File Type

application/pdf

DOI

10.1145/3168776.3168782

Other identifier(s)

2-s2.0-85041894823

Rights Holder(s)

มหาวิทยาลัยศรีนครินทรวิโรฒ

Bibliographic Citation

ACM International Conference Proceeding Series. (2017), p.48-51

Suggested Citation

Sueaseenak D., Sangsai P., Detyong P. The optimal algorithm of sub-symptom threshold exercise training for aural habilitation/rehabilitation. ACM International Conference Proceeding Series. (2017), p.48-51. doi:10.1145/3168776.3168782 Retrieved from: https://hdl.handle.net/20.500.14740/4011

Title

The optimal algorithm of sub-symptom threshold exercise training for aural habilitation/rehabilitation

Author(s)

Sueaseenak D.
 Sangsai P.
 Detyong P.

Abstract

This 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.

Subject(s)

Bioinformatics
 Character recognition
 Comparison study
 Decision process
 Exercise training
 Mel-frequency cepstral coefficients
 Optimal algorithm
 Performance testing
 Speech recognition systems
 Thai language
 Speech recognition

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URI

https://hdl.handle.net/20.500.14740/4011

Collections

Scopus: Year 1983-2021

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