Efficient and robust sound source recognition and localization is one of the basic techniques for humanoid robots in terms of reaction to environments. Due to the fixed sensor arrays and limited computation resources in humanoid robots, there comes challenge for sound source recognition and localization. This article proposes a sound source recognition and localization framework to realize real-time and precise sound source recognition and localization system using humanoid robots’ sensor arrays. The type of the audio is recognized according to the cross-correlation function. And steered response power-phase transform function in discrete angle space is used to search the sound source direction. The sound source recognition and localization framework presents a new multi-robots collaboration system to get the precise three-dimensional sound source position and introduces a distance weighting revision way to optimize the localization performance. Additionally, the experiment results carried out on humanoid robot NAO demonstrate that the proposed approaches can recognize and localize the sound source efficiently and robustly.

中文翻译：

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使用仿人机器人传感器阵列进行三维声源识别和定位的有效且稳健的方法

高效稳健的声源识别和定位是仿人机器人对环境做出反应的基本技术之一。由于仿人机器人传感器阵列固定，计算资源有限，声源识别和定位面临挑战。本文提出了一种声源识别与定位框架，利用仿人机器人的传感器阵列实现实时精准的声源识别与定位系统。根据互相关函数识别音频的类型。并利用离散角空间中的转向响应功率-相位变换函数来搜索声源方向。声源识别与定位框架提出了一种新的多机器人协作系统，以获取精确的三维声源位置，并引入距离加权修正方式来优化定位性能。此外，在仿人机器人 NAO 上进行的实验结果表明，所提出的方法可以有效且稳健地识别和定位声源。