扩音器阵列语音增强的广义随机原理及其在车载环境中的应用

R. Balan, J. Rosca, C. Beaugeant, Virginie Gilg, T. Fingscheidt
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引用次数: 1

摘要

在本文中,我们提出了一种新颖的解决方案,用于麦克风阵列语音增强系统,智能地使用多径环境来增强来自期望位置的信号。我们得到了一个统计原理,解释了以前已知的最优波束形成器的分解结果,并证明了类似的分解适用于其他新的最优估计器。我们的解决方案需要较低的计算负载,并且可以部署在大多数平台上。我们给出了真实数据的语音识别率,并在该数据库上比较了立体声和单声道解决方案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Generalized stochastic principle for microphone array speech enhancement and applications to car environments
In this paper we present novel solutions for microphone array speech enhancement systems that intelligently use the multipath environment to enhance signal coming from a desired location. We obtain a statistical principle that explains previously known factorization results of optimal beamformers, and proves a similar factorization holds for other new optimal estimators. Our solution requires a low computational load, and can be deployed on most of the platforms. We present speech recognition rates on real data, and compare a stereo versus a mono solution on this database.
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