语音去混响技术的研究进展与展望
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Speech Dereverberation: Review of State-of-the-Arts and Prospects
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    摘要:

    语音交互技术在实际的话音驱动应用中得到日益普及。然而,当声源距离传声器较远时,由于实际环境中混响现象的影响,语音交互的性能还远不能使人满意。针对混响问题,数十年来学者们不断地进行大量的研究,并提出了很多实用的方法。特别是近期兴起的在很大程度上改变语音处理格局的深度学习技术,在单通道去混响方面也取得了很多令人瞩目的效果。然而,目前系统性总结分析基于深度学习的去混响方法与经典算法之间联系的工作仍然比较匮乏。因此,本文对单通道语音去混响技术的发展脉络进行系统的梳理和总结,并讨论了有待进一步研究的开放问题。

    Abstract:

    Speech interaction technology is becoming increasingly popular in practical voice-driven applications. However, due to the inferences caused by reverberation in real-world environments, the performances of speech interaction in the distant-talking condition are far from being satisfactory. Decades of efforts are devoted to solving the reverberation problem and spawning a vast variety of practical methods. Recently, the deep learning technique, which is developing rapidly and has greatly reshaped the speech processing community, also acquires remarkable performance in speech dereverberation. However, a systematic analysis and summary of the inherent relationship between the recent deep learning based methods and the previous classical methods is rarely seen. As such, we give a comprehensive overview of the current and past development of single channel speech dereverberation. Then, the main challenges are discussed. Finally, we share some views of its future development.

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张雄伟 李轶南 郑昌艳 曹铁勇 孙蒙 闵刚.语音去混响技术的研究进展与展望[J].数据采集与处理,2017,32(6):1069-1081

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  • 在线发布日期: 2018-04-10