Residual-Based Excitation with Continuous FO Modeling in HMM-Based Speech Synthesis

摘要

In statistical parametric speech synthesis, creaky voice can cause disturbing artifacts. The reason is that standard pitch tracking algorithms tend to erroneously measure FO in regions of creaky voice. This pattern is learned during training of hidden Markov-models (HMMs). In the synthesis phase, false voiced/unvoiced decision caused by creaky voice results in audible quality degradation. In order to eliminate this phenomena, we use a simple continuous FO tracker which does not apply a strict voiced/unvoiced decision. In the proposed residual-based vocoder, Maximum Voiced Frequency is used for mixed voiced and unvoiced excitation. As all parameters of the vocoder are continuous, Multi-Space Distribution is not necessary during training the HMMs, which has been shown to be advantageous. Artifacts caused by creaky voice are eliminated with this speech synthesis system. A subjective listening test of English utterances has shown improvement over the traditional excitation.