MAD Military Audio Dataset

MAD stands for Military Audio Dataset, which was published by a research team from Korea National University of Transportation in 2024.A Military Audio Dataset for Situational Awareness and Surveillance", published in Nature.

This dataset is designed to support the training and evaluation of audio classification systems, especially in audio classification tasks related to military activities, such as gunfire, artillery fire, or explosions. The MAD dataset is extracted from multiple military videos and contains 8075 sound samples divided into 7 categories, totaling about 12 hours of audio.