Abstract / truncated to 115 words (read the full abstract)

The advent of multi-microphone setups on a plethora of commercial devices in recent years has generated a newfound interest in the development of robust microphone array signal processing methods. These methods are generally used to either estimate parameters associated with acoustic scene or to extract signal(s) of interest. In most practical scenarios, the sources are located in the far-field of a microphone array where the main spatial information of interest is the direction-of-arrival (DOA) of the plane waves originating from the source positions. The focus of this thesis is to incorporate robustness against either lack of or imperfect/erroneous information regarding the DOAs of the sound sources within a microphone array signal processing framework. The DOAs ... toggle 7 keywords

direction-of-arrival estimation localization convolutional neural networks deep learning speech enhancement microphone array processing spatial filtering


Chakrabarty, Soumitro
Friedrich-Alexander Universität Erlangen-Nürnberg
Publication Year
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June 15, 2020

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