| 英文摘要 |
Although many useful techniques have been developed, we still do not have a golden standard that can be applied to any kind of speech variation and any condition of the speech data available for training and adaptation. We need to focus on collecting rich and effective speech databases covering a wide range of variations, active learning for automatically selecting data for annotation, cheap, fast and good-enough transcription, and efficient supervised, semi-supervised, or unsupervised training/adaptation, based on advanced machine learning techniques. We also need to extend current efforts to understand more about human speech processing and the mechanism of natural speech variation. |
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