语音增强--现代方法回顾

IF 3.5 3区 计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Douglas O'Shaughnessy
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引用次数: 0

摘要

本文回顾了改善失真语音的技术,指出了常用方法的优缺点。从哪些特征应保留以保持自然度和可懂度的角度讨论了语音信号。增强方法包括经典的频谱减法和维纳滤波,以及最新的深度神经网络方法。讨论了找到近似感知语音质量的客观声学测量方法的困难。还提出了改进这些方法的建议。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Speech Enhancement—A Review of Modern Methods
A review of techniques to improve distorted speech is presented, noting the strengths and weaknesses of common methods. Speech signals are discussed from the point of view of which features should be preserved to retain both naturalness and intelligibility. Enhancement methods range from classical spectral subtraction and Wiener filtering to recent deep neural network approaches. The difficulty of finding objective acoustic measures that approximate perceptual speech quality is discussed. Suggestions to improve these methods are made.
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来源期刊
IEEE Transactions on Human-Machine Systems
IEEE Transactions on Human-Machine Systems COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-COMPUTER SCIENCE, CYBERNETICS
CiteScore
7.10
自引率
11.10%
发文量
136
期刊介绍: The scope of the IEEE Transactions on Human-Machine Systems includes the fields of human machine systems. It covers human systems and human organizational interactions including cognitive ergonomics, system test and evaluation, and human information processing concerns in systems and organizations.
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