  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.

Audio and Speech Processing;Sound