| Paper ID | E-3-3.2 |
| Paper Title |
SOURCE ENHANCEMENT FOR UNMANNED AERIAL VEHICLE RECORDING USING MULTI-SENSORY INFORMATION |
| Authors |
Benjamin Yen, Yusuke Hioka, Brian Mace, University of Auckland, New Zealand |
| Session |
E-3-3: Advanced Signal Processing and Machine Learning for Audio and Speech Applications |
| Time | Thursday, 10 December, 17:30 - 19:30 |
| Presentation Time: | Thursday, 10 December, 17:45 - 18:00 Check your Time Zone |
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All times are in New Zealand Time (UTC +13) |
| Topic |
Speech, Language, and Audio (SLA): Special Session: Advanced Signal Processing and Machine Learning for Audio and Speech Applications |
| Abstract |
A method to effectively capture desired sound signals from an unmanned aerial vehicle (UAV)-mounted audio recording system by utilising accurate rotor noise power spectral density (PSD) estimations of a UAV is proposed. The method seeks to improve the estimation accuracy and robustness of rotor noise PSD by incorporating UAV rotor characteristics in conjunction with microphone signals. Experiment results show rotor noise PSD estimation accuracy to within 5.5 dB log spectral distortion regardless of the presence of surrounding sound sources, with consistent ~28 dB improvement in signal-to-noise ratio, in particular, reduction of rotor noise from the noisy microphone recordings. |