PIAST: A Multimodal Piano Dataset with Audio, Symbolic and Text

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-spe...

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Published in:arXiv.org 2024-11
Main Authors: Bang, Hayeon, Choi, Eunjin, Finch, Megan, Doh, Seungheon, Lee, Seolhee, Lee, Gyeong-Hoon, Nam, Juhan
Format: Article
Language:English
Subjects:
Annotations
Audio data
Datasets
Information retrieval
Music
Pianos
Taxonomy
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Choi, Eunjin
Finch, Megan
Doh, Seungheon
Lee, Seolhee
Lee, Gyeong-Hoon
Nam, Juhan
description 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.
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subjects Annotations
Audio data
Datasets
Information retrieval
Music
Pianos
Taxonomy
title PIAST: A Multimodal Piano Dataset with Audio, Symbolic and Text
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