PIAST: A Multimodal Piano Dataset with Audio, Symbolic and Text
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Abstract (arXiv)
While piano music has become a significant area of study in Music Information Retrieval (MIR), there is a notable lack of datasets for piano solo music with text labels. To address this gap, we present PIAST (PIano dataset with Audio, Symbolic, and Text), a piano music dataset. Utilizing a piano-specific taxonomy of semantic tags, we collected 9,673 tracks from YouTube and added human annotations for 2,023 tracks by music experts, resulting in two subsets: PIAST-YT and PIAST-AT. Both include audio, text, tag annotations, and transcribed MIDI utilizing state-of-the-art piano transcription and beat tracking models. Among many possible tasks with the multi-modal dataset, we conduct music tagging and retrieval using both audio and MIDI data and report baseline performances to demonstrate its potential as a valuable resource for MIR research.
Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 18 of its 29 references that are in the map. First posted on arXiv 4 Nov 2024.
Builds on
18 of 29 references.
References · 18
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6 more
- 2022Toward Universal Text-to-Music Retrievalcited by 18
- 2019Zero-shot Learning for Audio-based Music Classification and Taggingcited by 13
- 2022Pop2Piano : Pop Audio-based Piano Cover Generationcited by 10
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Citing papers per year: 2025: 1; 2026: 1.
2 papers.