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

arXiv: https://arxiv.org/abs/2206.05606 · HTML: https://mlsanity.com/paper/2206.05606/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 11 Jun 2022.

## Built on by (most cited first, 1 of 1)

- [Learning Robust Spatial Representations from Binaural Audio through Feature Distillation](https://mlsanity.com/paper/2508.20914/) (2025)

## Abstract (arXiv)

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.