Signal-Aware Broadband DOA Estimation Using Attention Mechanisms

Mack W, Bharadwaj U, Chakrabarty S, Habets E (2020)


Publication Type: Conference contribution

Publication year: 2020

Journal

Publisher: Institute of Electrical and Electronics Engineers Inc.

Book Volume: 2020-May

Pages Range: 4930-4934

Conference Proceedings Title: ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings

Event location: Barcelona, ESP

ISBN: 9781509066315

DOI: 10.1109/ICASSP40776.2020.9053658

Abstract

We refer to direction-of-arrivals (DOAs) estimation of a user-defined subset of directional (desired) sound sources as signal-aware DOA estimation. Source selection, thereby, can be achieved with time-frequency masks to apply attention to TF bins dominated by desired sources. With deep neural networks (DNNs), another option is to train the DNN to estimate the DOAs only of specific classes, like speech, and disregard the DOAs of other classes. Consequently, changing the desired classes requires retraining the DNN. Also, the mask-based approaches are trained for sources known prior to DNN training. To obtain a flexible signal-aware DOA estimator, we propose to use binary mask attention with a DNN for multi-source DOA estimation trained with artificial noise. The desired sources are determined via binary masks, which allows a redefinition by changing the masks. Consequently, the DOA estimator is independent of the desired sources. We experiment with attention in form of oracle and estimated binary masks.

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How to cite

APA:

Mack, W., Bharadwaj, U., Chakrabarty, S., & Habets, E. (2020). Signal-Aware Broadband DOA Estimation Using Attention Mechanisms. In ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings (pp. 4930-4934). Barcelona, ESP: Institute of Electrical and Electronics Engineers Inc..

MLA:

Mack, Wolfgang, et al. "Signal-Aware Broadband DOA Estimation Using Attention Mechanisms." Proceedings of the 2020 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2020, Barcelona, ESP Institute of Electrical and Electronics Engineers Inc., 2020. 4930-4934.

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