Model based stress decision method

This paper proposes an effective decision method focused to evaluate the “stress position”. Conventional methods usually extract the acoustic parameters and compare them to reference in absolute scale, adversely producing unstable results as testing condition changes. To cope with the environmental dependency, the proposed method is designed to be model-based that determines the stressed interval by making relative comparison over candidates. The stressed/unstressed models are then induced from normal phone models by adaptive training. The experimental results indicate that the proposed method is promising and that it is useful for automatic detection of stress positions. The results also show that generating the stressed/unstressed model by adaptive training is effective.