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

非アルコール性脂肪肝炎マウスモデルにおいて、ペリオスチンアンチセンス核酸は肝脂肪化と線維化を抑制する

内容の要旨、審査の要旨広島大学(Hiroshima University)博士(医学)Doctor of Philosophy in Medical Sciencedoctora

Runoff Analysis Using a Deep Neural Network

Source: ICHE Conference Archive - https://mdi-de.baw.de/icheArchive

小肝癌の病理肉眼型に対するGd-EOB-DTPA造影MRIと造影超音波を組み合わせた予測画像診断の有用性

内容の要旨 , 審査の要旨広島大学(Hiroshima University)博士(医学)Doctor of Philosophy in Medical Sciencedoctora