Collapsed speech segment detection and suppression for WaveNet vocoder

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. To address this problem, we propose a technique to automatically detect collapsed speech segments. Moreover, to refine the detected segments, we also propose a waveform generation technique for WaveNet using a linear predictive coding constraint. Verification and subjective tests are conducted to investigate the effectiveness of the proposed techniques. The verification results indicate that the detection technique can detect most collapsed segments. The subjective evaluations of voice conversion demonstrate that the generation technique significantly improves the speech quality while maintaining the same speaker similarity.Comment: 5 pages, 6 figures. Proc. Interspeech, 201

Knowledge Sharing in Virtual Community: The Comparison between Contributors and Lurkers

Internet-based virtual communities are growing with an unprecedented rate. Virtual communities have been viewed as platforms for sharing knowledge. The present study proposed an integrated model by investigating social capital and motivational factors that would influence the knowledge sharing attitude of members. Data were collected from 207 professional virtual community users (including 53 contributors and 154 lurkers). The results showed that trust and pro-sharing norms mediate the relationship between shared understanding and knowledge sharing attitude. Enjoy helping, commitment, and community-related outcome expectations enhance contributors’ attitudes toward knowledge sharing. When lurkers perceived more reciprocity in their communities and expect more community-related outcome, they incline to sharing knowledge with others. The implications of these results are discussed