Comparison of different techniques on Thai speech recognition
Visarut Ahkuputra, SOMCHAI JITAPUNKUL, Ekkarit Maneenoi, Sawit Kasuriya, P. Amornkul · 2002
This paper introduces the comparison between Thai isolated word speech recognition techniques using the Hidden Markov Model, the Modified Backpropagation Neural Network, and the Fuzzy-Neural Network. The recognition has been made on the ten isolated Thai numerals from zero to nine under the same system configuration for all the approaches. The 15-state left-to-right discrete hidden Markov model in cooperation with the vector quantization technique was compared with the multilayer network using error backpropagation, the modified backpropagation, and also with the fuzzy-neural network with the same configuration. The recognition accuracy using hidden Markov model, neural network, modified neural network and fuzzy-neural network approaches are 84.250 percent, 73.030 percent, 78.000 percent, and 78.300 percent respectively.