基于深度学习的语音识别技术现状与展望
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Deep Learning for Speech Recognition: Review of State-of-the-Arts Technologies and Prospects
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    摘要:

    首先对深度学习的发展历史以及概念进行简要的介绍。然后回顾最近几年基于深度学习的语音识别的研究进展。这一部分内容主要分成以下5点进行介绍:声学模型训练准则,基于深度学习的声学模型结构,基于深度学习的声学模型训练效率优化,基于深度学习的声学模型说话人自适应和基于深度学习的端到端语音识别。最后就基于深度学习的语音识别未来可能的研究方向进行展望。

    Abstract:

    In this paper, deep learning is briefly introduced. Then, a review of the research progress of deep learning based speech recognition is presented from the following five points: Training criterions for deep learning based acoustic models, different model architectures for deep learning based speech recognition acoustic modeling, scalable and distributed optimization methods for deep learning based acoustic model training, speaker adaptation for deep learning based acoustic model, and deep leaning based end-to-end speech recognition. At the end of this paper, the future possible research points of deep learning based speech recognition are also proposed.

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戴礼荣 张仕良 黄智颖.基于深度学习的语音识别技术现状与展望[J].数据采集与处理,2017,32(2):221-231

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  • 在线发布日期: 2017-04-27