We present Task 5 of the DCASE 2025 Challenge: an Audio Question Answering (AQA) benchmark spanning multiple domains of sound understanding. This task defines three QA subsets (Bioacoustics, Temporal Soundscapes, and Complex QA) to test audio-language models on interactive question-answering over diverse acoustic scenes. We describe the dataset composition (from marine mammal calls to soundscapes and complex real-world clips), the evaluation protocol (top-1 accuracy with answer-shuffling robustness), and baseline systems (Qwen2-Audio-7B, AudioFlamingo 2, Gemini-2-Flash). Preliminary results on the development set are compared, showing strong variation across models and subsets. This challenge aims to advance the audio understanding and reasoning capabilities of audio-language models toward human-level acuity, which are crucial for enabling AI agents to perceive and interact about the world effectively.
View on arXiv@article{yang2025_2505.07365,
title={ Multi-Domain Audio Question Answering Toward Acoustic Content Reasoning in The DCASE 2025 Challenge },
author={ Chao-Han Huck Yang and Sreyan Ghosh and Qing Wang and Jaeyeon Kim and Hengyi Hong and Sonal Kumar and Guirui Zhong and Zhifeng Kong and S Sakshi and Vaibhavi Lokegaonkar and Oriol Nieto and Ramani Duraiswami and Dinesh Manocha and Gunhee Kim and Jun Du and Rafael Valle and Bryan Catanzaro },
journal={arXiv preprint arXiv:2505.07365},
year={ 2025 }
}