The effect of speech denoising algorithms on sound source localization for humanoid robots

Georgios Athanasopoulos, Tomas Dekens, H. Brouckxon, W. Verhelst
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引用次数: 6

Abstract

In this paper we study the suitability and performance of four major speech denoising algorithms as weighting functions for the Generalized Cross-Correlation (GCC) and discuss the role of the microphones' frequency response on the localization estimates. An evaluation is made with the humanoid robot Nao. Moving away from simulated environments, we look at the performance of sound source localization under different in-system and ambient noise conditions. We also present a time delay of arrival (TDOA) / GCC based sound source localization method for real-world humanoid robots which was used for our experiments. This method addresses the robot's shape influence by utilizing a pre-measured set of TDOAs.
语音去噪算法对仿人机器人声源定位的影响
本文研究了四种主要的语音去噪算法作为广义互相关(GCC)加权函数的适用性和性能,并讨论了麦克风的频率响应对定位估计的影响。用仿人机器人Nao进行了评价。远离模拟环境,我们研究了不同系统内和环境噪声条件下声源定位的性能。我们还提出了一种基于到达时间延迟(TDOA) / GCC的真实人形机器人声源定位方法,并将其用于我们的实验。该方法通过利用一组预先测量的tdoa来解决机器人形状的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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