Malay Language Speech Recogniser with Hybrid Hidden Markov Model and Artificial Neural Network(HMM/ANN)

Abstract

There are many artificial intelligence approaches used in the development of Automatic Speech Recognition (ASR), and hybrid approach is one of them. The common hybrid method in speech recognition is the combination of Hidden Markov Model (HMM) and Artificial Neural Network (ANN). The hybrid HMM/ANN is able to combine the strength of HMM in sequential modeling structure and ANN in pattern classification. Thus, this paper proposed a speaker independent and continuous Malay language speech recogniser by using the hybrid HMM/ANN method. In addition to that, this paper presents a study on Standard Malay’s phonetic and phonology to help in the recognition of Malay words. The CSLU toolkit is utilized for building the recogniser, and the experimental results showed that the proposed HMM/ANN model outperformed the conventional HMM model. The performances of the recognisers are measured in term of word accuracy and sentence accuracy. Index