On the process of coarticulation for a CELP-based Chinese text-to-speech system using LSP frequencies

This study proposes a novel approach based on a Bayesian network and the LSP frequencies to generate syllable prosody and the coarticulation between two concatenated syllables respectively. The Bayesian network is employed to model the relation between the prosodic information and the linguistic features. Given a Chinese character sequence, the Bayesian network can provide appropriate prosodic information, including pitch contour, syllable intensity, syllable duration and pause duration. Furthermore, the coarticulation is generated by adjusting the LSP frequencies in a CELP-based synthesizer. The synthesized speech is tested on twenty subjects. The test results indicate that the average correct rate is 95.8% for intelligibility, and the mean opinion score (MOS) is 3.2 for naturalness.