Robust Pitch Extraction Method for the HMM-Based Speech Synthesis System

Abstract

This letter proposes an efficient method for extracting pitch from speech signals for the hidden Markov model (HMM)-based speech synthesis system (HTS). In the proposed method, voicing detection and pitch estimation is performed using the mean signal obtained from continuous wavelet transform coefficients. The proposed pitch extraction method is integrated in the HMM-based speech synthesis system. The Performance of the proposed method is evaluated on CMU Arctic and Keele databases. Both objective and subjective evaluation results show that the quality of speech synthesized with the proposed pitch estimation method is much better compared with HMM-based speech synthesis systems developed using the state-of-the-art pitch extraction methods, namely, robust algorithm for pitch tracking and speech transformation and representation using adaptive interpolation of weighted spectrum employed in the HTS.