Speech enhancement using ego-noise references with a microphone array embedded in an unmanned aerial vehicle

TL;DR

This paper presents a speech enhancement method for UAVs using ego-noise references with a microphone array, improving speech intelligibility and quality in noisy UAV environments through a novel PK-MWF approach.

Contribution

The paper introduces a new PK-MWF method utilizing ego-noise references from propeller microphones for enhanced speech extraction on UAVs.

Findings

PK-MWF outperforms standard MWF in speech intelligibility and quality

Experimental results show improved STOI and PESQ scores

Method maintains similar SNR improvement as standard approaches

Abstract

A method is proposed for performing speech enhancement using ego-noise references with a microphone array embedded in an unmanned aerial vehicle (UAV). The ego-noise reference signals are captured with microphones located near the UAV's propellers and used in the prior knowledge multichannel Wiener filter (PK-MWF) to obtain the speech correlation matrix estimate. Speech presence probability (SPP) can be estimated for detecting speech activity from an external microphone near the speech source, providing a performance benchmark, or from one of the embedded microphones, assuming a more realistic scenario. Experimental measurements are performed in a semi-anechoic chamber, with a UAV mounted on a stand and a loudspeaker playing a speech signal, while setting three distinct and fixed propeller rotation speeds, resulting in three different signal-to-noise ratios (SNRs). The recordings obtained and made available online are used to compare the proposed method to the use of the standard multichannel Wiener filter (MWF) estimated with and without the propellers' microphones being used in its formulation. Results show that compared to those, the use of PK-MWF achieves higher levels of improvement in speech intelligibility and quality, measured by STOI and PESQ, while the SNR improvement is similar.