2021 IEEE International Conference on Acoustics, Speech and Signal Processing

6-11 June 2021 • Toronto, Ontario, Canada

Extracting Knowledge from Information

2021 IEEE International Conference on Acoustics, Speech and Signal Processing

6-11 June 2021 • Toronto, Ontario, Canada

Extracting Knowledge from Information
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Paper Detail

Paper IDAUD-10.4
Paper Title ON THE PREPARATION AND VALIDATION OF A LARGE-SCALE DATASET OF SINGING TRANSCRIPTION
Authors Jun-You Wang, Jyh-Shing Roger Jang, National Taiwan University, Taiwan
SessionAUD-10: Music Information Retrieval and Music Language Processing 2: Singing Voice
LocationGather.Town
Session Time:Wednesday, 09 June, 14:00 - 14:45
Presentation Time:Wednesday, 09 June, 14:00 - 14:45
Presentation Poster
Topic Audio and Acoustic Signal Processing: [AUD-MIR] Music Information Retrieval and Music Language Processing
IEEE Xplore Open Preview  Click here to view in IEEE Xplore
Abstract This paper proposes a large-scale dataset for singing transcription, along with some methods for fine-tuning and validating its contents. The dataset is named MIR-ST500, which consists of more than 160,000 notes from 500 pop songs. To create this large-scale dataset, we set some labeling criteria and ask non-experts to label notes. We also perform some adjustments on the annotation to correct minor errors. Finally, to validate the dataset, we train a singing transcription model on MIR-ST500 dataset and evaluate it on various datasets. The result shows that we can certainly construct a better singing transcription model for various purposes using MIR-ST500, which is properly labeled and validated.