Isolated malay speech recognition using Hidden Markov Models

Abstract

The study aims to develop an automated isolated word speech recognition for Malay language that relies heavily on the well known and widely used statistical method in characterizing the speech pattern, the Hidden Markov Model (HMM). This paper discusses the development and implementation of an isolated Malay word speech recognition system using HMM as the acoustic model. This research focuses on isolated 5 phonemes word structure such as empat (four), lapan (eight), rekod (record), tidak (no), tujuh (seven) and tutup (close). The proposed system is relatively successful where it can identify spoken word at 88% recognition rate which is an acceptable rate of accuracy for speech recognition.