MMAU
dataset·general audio reasoning·active
A multi-domain benchmark of expert audio understanding and reasoning spanning speech, environmental sound and music.
Verified facts
| Official site | https://sakshi113.github.io/mmau_homepage/ ↗ |
|---|---|
| Geography | United States |
| size | skills: 27 · questions: 10000 · source corpora: 13 |
| scope | Information extraction and complex reasoning across speech, sound and music. |
| genres | multiple |
| license | mixed/source-specific |
| steward | University of Maryland-led collaboration |
| creators | MMAU authors |
| languages | primarily English questions; source audio varies |
| modalities | audio; multiple-choice questions; answers; skill taxonomy |
| geographies | Global |
| access method | Official project links code and data. |
| intended uses | audio-language model evaluation; audio reasoning evaluation |
| consent claims | Inherited from source corpora; annotator terms not verified. |
| related papers | MMAU: A Massive Multi-Task Audio Understanding and Reasoning Benchmark |
| annotation method | Expert-oriented question design with answer choices and skill labels. |
| collection method | Questions and audio are assembled across thirteen source corpora. |
| provenance claims | Official page documents source domains and benchmark organization. |
| current availability | Project page and artifacts available. |
| commercial use limits | Depends on each source corpus. |
| us market scope basis | Publicly available or materially used in US-facing music/audio-AI research. |
| limitations biases disputes | Multiple-choice accuracy is not equivalent to open-ended auditory competence.; Music is only one of three domains. |
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