An architecture of HMM-based isolated-word speech recognition with tone detection function

In an architecture of speech recognition for some languages (such as Thai, Chinese, and so on) that tone plays a key role in meaning classification, tone detection function is required in order to guarantee a correct word recognition. This paper proposes an architecture of HMM-based isolated-word speech recognition with tone detection function. In this architecture, tone detection function is added into each computation process of series architecture and each parallel computation of scalable architecture. To evaluate the performance of the proposed method, the experiment is set and performed with 29 Thai words selected from TV remote control commands and 10 Thai indistinct tone classification words. The results reveal 4.94% improvement of accuracy rate for remote control commands and 10.75% for indistinct tone classification words comparing with the conventional architecture.