Deep Learning Models for Single-Channel Speech Enhancement on Drones

Author:

Mukhutdinov Dmitrii1,Alex Ashish1,Cavallaro Andrea1ORCID,Wang Lin1ORCID

Affiliation:

1. Centre for Intelligent Sensing, Queen Mary University of London, London, U.K

Funder

U.K. Engineering and Physical Sciences Research Council

ARTEMIS-JU and the U.K. Technology Strategy Board (Innovate U.K.) through the COPCAMS Project

Pilot Research Project of EPSRC UK Acoustics Network Plus

use of time on Tier 2 HPC Facility JADE2, funded by EPSRC

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Reference71 articles.

1. Aerial Drones with Location-Sensitive Ears

2. The INTERSPEECH 2020 deep noise suppression challenge: Datasets, subjective speech quality and testing framework;reddy;arXiv 2001 08662,2020

3. Beamforming-Based Acoustic Source Localization and Enhancement for Multirotor UAVs

4. The Diverse Environments Multi-channel Acoustic Noise Database (DEMAND): A database of multichannel environmental noise recordings

5. Source enhancement for unmanned aerial vehicle recording using multi-sensory information;yen;Proc Asia–Pacific Signal Inf Process Assoc Annu Summit Conf,2020

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