Collapsed speech segment detection and suppression for WaveNet vocoder

Understand

In this paper, we propose a technique to alleviate the quality degradation caused by collapsed speech segments sometimes generated by the WaveNet vocoder.

• The effectiveness of the WaveNet vocoder for generating natural speech from acoustic features has been proved in recent works.
• However, it sometimes generates very noisy speech with collapsed speech segments when only a limited amount of training data is available or significant acoustic mismatches exist between the training and testing data.
• Such a limitation on the corpus and limited ability of the model can easily occur in some speech generation applications, such as voice conversion and speech enhancement.