RealDESED: A Real-World Domestic Sound Event Detection Benchmark
RealDESED is a new benchmark dataset for domestic sound event detection, featuring 5,710 real-world audio recordings from 652 participants' homes. The dataset includes 15 sound classes, multi-annotator labels, and extensive metadata, aiming to better reflect the variability and complexity of real domestic environments compared to simulated datasets. A transformer-based baseline achieves a macro-averaged PSDS1 score of 0.731 on the test set.
Why it matters: RealDESED offers a realistic and diverse dataset that can drive the development of more robust sound event detection systems for real-world home environments.
Full story at: arXiv Audio and Speech Processing ↗