In this article, we examine microphone array systems from an architectural perspective. Such systems begin with microphone selection and the acoustic design of the array enclosure. We then present a general block diagram and explore traditional signal processing algorithms used in each functional component: sound source localization, beam selection, beamforming, and spatial filtering. Following a historical overview of algorithmic development, we discuss the application of machine learning and artificial intelligence techniques in microphone array signal processing. The article is illustrated with examples drawn from the authors' experience designing microphone array systems for products such as RoundTable, Kinect for Xbox 360 and Xbox One, HoloLens and HoloLens 2, as well as the integrated microphone array support in Windows.
Tashev et al. (Wed,) studied this question.
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