摘要
首先对深度学习进行简要的介绍,然后就其在语音信号与信息处理研究领域的主要研究方向,包括语音识别、语音合成、语音增强的研究进展进行了详细的介绍。语音识别方向主要介绍了基于深度神经网络的语音声学建模、大数据下的模型训练和说话人自适应技术;语音合成方向主要介绍了基于深度学习模型的若干语音合成方法;语音增强方向主要介绍了基于深度神经网络的若干典型语音增强方案。最后对深度学习在语音信与信息处理领域的未来可能的研究热点进行展望。
Deep learning is briefly introduced at first. Then, a review on the research progress of deep speech signal and information processing is provided along the main research branches including speech recognition, speech synthesis and speech enhancement. For speech recogni- tion, the acoustic modeling methods based on deep neural network（DNN）, DNN model train- ing technologies for big speech data and DNN speaker adaptation methods are introduced. For speech synthesis, several speech synthesis methods based on models in deep learning are sum- marized. For speech enhancement, a couple of typical DNN based speech enhancement frame- works are presented. Finally, the possible future research points of deep speech signal and in- formation processing are discussed.
出处
《数据采集与处理》
CSCD
北大核心
2014年第2期171-179,共9页
Journal of Data Acquisition and Processing
基金
国家重点基础研究发展计划("九七三"计划)(2012CB326405)资助项目
国家自然科学基金(61273264)资助项目
关键词
深度学习
深度神经网络
语音识别
语音合成
语音增强
deep learning
deep neural network
speech recognition
speech synthesis
speech enhancement
