Multi-Domain Audio Question Answering Benchmark Toward Acoustic Content Reasoning
On the map: LLM reasoning → Audio-language model reasoning
Abstract (arXiv)
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.
Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). Placed in Audio-language model reasoning, one of 17 directions in LLM reasoning. Builds on 18 of its 26 references that are in the map. First posted on arXiv 12 May 2025.
Builds on
18 of 26 references.
Closest ancestors · 3
Same direction, newest first
- 2025Audio Flamingo 2: An Audio-Language Model with Long-Audio Understanding and Expert Reasoning Abilities6 Mar
- 2024MMAU: A Massive Multi-Task Audio Understanding and Reasoning Benchmark24 Oct
- 2024GAMA: A Large Audio-Language Model with Advanced Audio Understanding and Complex Reasoning Abilities17 Jun
Other references · 15
- 2019Sentence-BERT: Sentence Embeddings using Siamese BERT-Networkscited by 9,049
- 2022Robust Speech Recognition via Large-Scale Weak Supervisioncited by 3,972
- 2023Qwen Technical Reportcited by 3,273
- 2024Qwen2-Audio Technical Reportcited by 543
- 2023SALMONN: Towards Generic Hearing Abilities for Large Language Modelscited by 492
- 2023Pengi: An Audio Language Model for Audio Taskscited by 217
- 2024AIR-Bench: Benchmarking Large Audio-Language Models via Generative Comprehensioncited by 215
- 2024Audio Flamingo: A Novel Audio Language Model with Few-Shot Learning and Dialogue Abilitiescited by 183
- 2024MiraData: A Large-Scale Video Dataset with Long Durations and Structured Captionscited by 144
- 2024AudioBench: A Universal Benchmark for Audio Large Language Modelscited by 124
- 2023Generative Speech Recognition Error Correction with Large Language Models and Task-Activating Promptingcited by 71
- 2019A multi-room reverberant dataset for sound event localization and detectioncited by 18
3 more
Built on by
Citing papers per year: 2025: 2; 2026: 3.
5 papers.
- 2025OmniVinci: Enhancing Architecture and Data for Omni-Modal Understanding LLMcited by 53
- 2025AURA Score: A Metric For Holistic Audio Question Answering Evaluationcited by 0
- 2026Eureka-Audio: Triggering Audio Intelligence in Compact Language Modelscited by 0
- 2026Tracing Audio Grounding and Answer Selection in Audio LLMscited by 0
- 2026Augmenting Large Audio-Language Models with Frame-Level Grounding for Fine-Grained Temporal Perceptioncited by 0
- 2026Augmenting Large Audio-Language Models with Frame-Level Grounding for Fine-Grained Temporal Perception14 Sep 2026
- 2026Tracing Audio Grounding and Answer Selection in Audio LLMs4 Sep 2026
- 2026Eureka-Audio: Triggering Audio Intelligence in Compact Language Models15 Feb 2026
- 2025OmniVinci: Enhancing Architecture and Data for Omni-Modal Understanding LLM17 Oct 2025
- 2025AURA Score: A Metric For Holistic Audio Question Answering Evaluation6 Oct 2025
Similar, not cited
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- 2024Audiopedia: Audio QA with Knowledge
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- 2025MMAR: A Challenging Benchmark for Deep Reasoning in Speech, Audio, Music, and Their Mix
- 2025CMDAR: A Chinese Multi-scene Dynamic Audio Reasoning Benchmark with Diverse Challenges
- 2025Audio Flamingo Sound-CoT Technical Report: Improving Chain-of-Thought Reasoning in Sound Understanding
- 2024Enhancing Temporal Understanding in Audio Question Answering for Large Audio Language Models
- 2026SEABED: SouthEast Asian Benchmark for Evaluating Audio Reasoning