Speech enhancement algorithms for multimedia applications

多媒体应用的语音增强算法

• 批准号: 283137-2009
• 负责人: Benesty, Jacob
• 金额: $ 2.62万
• 依托单位: Institut national de la recherche scientifique
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2015
• 资助国家: 加拿大
• 起止时间: 2015-01-01 至 2016-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=571318
• 关键词: Speech; enhancement; algorithms; multimedia; applications

Speech enhancement plays a fundamental role in many applications such as teleconferencing systems, speech recognizers, human-machine interfaces, hands-free communications, mobile phones, and hearing aids. Indeed, the noise is around us and everywhere. So when a signal of interest (usually speech) is picked up by a microphone, it is always contaminated by noise, reverberation, and other undesired signals. The objective is then to clean up the noisy signal with digital signal processing tools without damaging much the desired speech signal. The problem of speech enhancement is an old one and has been around for more than 40 years. This should not come as a surprise since, contrary to what some people may believe, it is a very difficult problem for mainly two reasons. First, the nature and characteristics of the noise signals can change dramatically in time and application to application. It is therefore laborious to find versatile algorithms that really work in different practical environments. Second, the performance measure can also be defined differently for each application. Two perceptual criteria are widely used to measure the performance: quality and intelligibility. While the former is subjective (it reflects individual preferences of listeners), the latter is objective (it gives the percentage of words that could be correctly identified by listeners). It is very hard to satisfy both at the same time. So this research proposal aims at developing the next-generation speech enhancement algorithms with one and, especially, multiple microphones (or microphone arrays) with the clear objective to reduce the noise and other interference signals as much as possible with little (or no) distortion of the desired speech signal. In other words, we will try to improve the quality as much as possible without affecting the intelligibility. We will also try to develop practical algorithms that can be easy to use and easy to tune in the real world and for most applications. To achieve this goal, we will rely on some strong ideas and results we have developed recently.

语音增强在诸如电话会议系统、语音识别器、人机接口、免提通信、移动的电话和助听器的许多应用中起着基本作用。事实上，噪音就在我们周围，到处都是。因此，当麦克风拾取感兴趣的信号（通常是语音）时，它总是受到噪声，混响和其他不需要的信号的污染。然后，目标是用数字信号处理工具清除噪声信号，而不会对期望的语音信号造成太大的损害。 语音增强是一个古老的问题，已经存在了40多年。这不应令人感到意外，因为与某些人可能认为的相反，这是一个非常困难的问题，主要有两个原因。首先，噪声信号的性质和特征可以随时间和应用而显著变化。因此，要找到真正适用于不同实际环境的通用算法是很困难的。其次，性能度量也可以针对每个应用程序进行不同的定义。两个感知标准被广泛用于衡量性能：质量和可懂度。前者是主观的（它反映了听众的个人偏好），后者是客观的（它给出了听众可以正确识别的单词的百分比）。很难同时满足两者。 因此，本研究的目的是开发下一代语音增强算法与一个，特别是，多个麦克风（或麦克风阵列）的明确目标，以减少噪声和其他干扰信号尽可能少（或没有）失真的期望的语音信号。换句话说，我们将在不影响清晰度的情况下尽可能提高质量。我们还将尝试开发实用的算法，这些算法可以在真实的世界和大多数应用中易于使用和调整。为了实现这一目标，我们将依靠我们最近开发的一些强有力的想法和成果。