A study on pitch pattern generation using HMM-based statistical information

This paper describes a novel pitch pattern generation method for speech synthesis using Hidden Markov Models (HMMs). In the proposed method, the F0 contours of minor phrase are modeled by HMMs (pitch-HMMs). The pitch-HMMs are trained using F0 and 1F0 considering phonetic environments (e.g. accent type, mora count, mora position, phonemic category, etc.). To evaluate the pitch-HMMs, accent identification experiments are performed. The results indicate that the pitch-HMMs can capture the movement in F0 contours appropriately. In the F0 contour generation experiments, the proposed method yields an averaged root mean square error of 132cent (equivalent to 9.2Hz at 120Hz) between the original and the generated F0 contours. Furthermore, an application of the proposed method to text-to-speech system is also discussed. 1. INTRODUCTION A good generation model of fundamental frequency (F0 contours) is essential for speech systems. Recently, several methods of F0 contour modeling based on stati...