DocumentCode :
1662769
Title :
Thai speech recognition using Neuro-fuzzy system
Author :
Srijiranon, Krittakom ; Eiamkanitchat, Narissara
Author_Institution :
Dept. of Comput. Eng., Chiang Mai Univ., Chiang Mai, Thailand
fYear :
2015
Firstpage :
1
Lastpage :
6
Abstract :
There are many popular algorithms to recognize the human voice. The good algorithm not only results the high recognition accuracy, but also robust to noises. Several experiments are done in this research to verify the performance of the Neuro-fuzzy system to recognize the human voice. Eight words in Thai language recorded in a different environment, syllable and pronunciations are used as a data set in the experiments. All words are in machine command category, the meaning of words such as forward, back, left, right and so on, with the purpose of applying to some instrument for disabled people in the future. The preliminary results show that each factor has different effects to the recognition accuracy. However the experimental results show that the Neuro-fuzzy system is quite robust to noise and can yield the higher recognition results compare with other popular algorithms. The methodology of speech recognition proposed in this paper can be one of the best alternative choices to apply to a relative work in the future.
Keywords :
fuzzy neural nets; handicapped aids; natural language processing; speech recognition; Thai language; Thai speech recognition; disabled people; human voice recognition algorithms; machine command category; neuro-fuzzy system; pronunciations; Accuracy; Classification algorithms; Feature extraction; Neural networks; Noise; Prediction algorithms; Speech recognition; Neuro-Fuzzy System; Perceptual Linear Predictive (PLP); Thai Speech Recognition;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON), 2015 12th International Conference on
Conference_Location :
Hua Hin
Type :
conf
DOI :
10.1109/ECTICon.2015.7207075
Filename :
7207075
Link To Document :
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