datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
MTG_QGHumMusQA
HumMusQA: A Human-written Music Understanding QA Benchmark Dataset
Authors: Benno Weck, Pablo Puentes, Andrea Poltronieri, Satyajeet Prabhu, Dmitry Bogdanov
HumMusQA is a multiple-choice question answering dataset designed to test music understanding in Large Audio-Language Models (LALMs).
Dataset Highlights
✍️ 320 hand-written multiple-choice questions curated and validated by experts with musical training
🎵 108 Creative Commons-licensed music tracks sourced from… See the full description on the dataset page: https://huggingface.co/datasets/mtg-upf/HumMusQA.mtg-rules-qa