Go to NeurIPS 2025 Datasets and Benchmarks Track homepageDroneAudioset: An Audio Dataset for Drone-based Search and Rescue
Keywords: drone audition, noisy audio, search and rescue, audio dataset
TL;DR: We develop "DroneAudioset", a dataset that provides audio recordings from drone-mounted microphones to inform noise suppression and sound classification techniques for drone-audition based human presence detection in search and rescue missions.
Abstract: Unmanned Aerial Vehicles (UAVs) or drones, are increasingly used in search and rescue missions to detect human presence. Existing systems primarily leverage vision-based methods which are prone to fail under low-visibility or occlusion. Drone-based audio perception offers promise but suffers from extreme ego-noise that masks sounds indicating human presence.
Existing datasets are either limited in diversity or synthetic, lacking real acoustic interactions, and there are no standardized setups for drone audition. To this end, we present DroneAudioset (The dataset is publicly available at https://huggingface.co/datasets/ahlab-drone-project/DroneAudioSet/ under the MIT license), a comprehensive drone audition dataset featuring 23.5 hours of annotated recordings, covering a wide range of signal-to-noise ratios (SNRs) from -57.2 dB to -2.5 dB, across various drone types, throttles, microphone configurations as well as environments. The dataset enables development and systematic evaluation of noise suppression and classification methods for human-presence detection under challenging conditions, while also informing practical design considerations for drone audition systems, such as microphone placement trade-offs, and development of drone noise-aware audio processing. This dataset is an important step towards enabling design and deployment of drone-audition systems.
Croissant File: json
Dataset URL: https://huggingface.co/datasets/ahlab-drone-project/DroneAudioSet
Primary Area: Applications of Datasets & Benchmarks for in speech and audio
Submission Number: 508
Loading