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Signal-informed DNN-based DOA Estimation combining an External Microphone and GCC-PHAT Features

2022-06-11 20:14:37
Ulrik Kowalk, Simon Doclo, Joerg Bitzer
arXiv_SD
       
Abstract

Aiming at estimating the direction of arrival (DOA) of a desired speaker in a multi-talker environment using a microphone array, in this paper we propose a signal-informed method exploiting the availability of an external microphone attached to the desired speaker. The proposed method applies a binary mask to the GCC-PHAT input features of a convolutional neural network, where the binary mask is computed based on the power distribution of the external microphone signal. Experimental results for a reverberant scenario with up to four interfering speakers demonstrate that the signal-informed masking improves the localization accuracy, without requiring any knowledge about the interfering speakers.

Abstract (translated)

URL

https://arxiv.org/abs/2206.05606

PDF

https://arxiv.org/pdf/2206.05606.pdf

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