ReconVAT: A Semi-Supervised Automatic Music Transcription Framework for Low-Resource Real-World Data-Reference-Cited by-同舟云学术

ReconVAT: A Semi-Supervised Automatic Music Transcription Framework for Low-Resource Real-World Data

Published:2021-10-17 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 29th ACM International Conference on Multimedia
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Author:

Cheuk Kin Wai¹,Herremans Dorien¹,Su Li²

Affiliation:

1. Singapore University of Technology and Design, Singapore, Singapore

2. Academia Sinica, Taiwan, Taiwan Roc

Funder

Ministry of Education (Singapore)

Agency for Science, Technology and Research (A*STAR)

Singapore University of Technology and Design

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3474085.3475405

Reference47 articles.

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2. Automatic Music Transcription;Benetos Emmanouil;An Overview. IEEE Signal Processing Magazine,2019

3. Automatic music transcription: challenges and future directions;Benetos Emmanouil;Journal of Intelligent Information Systems,2013

4. Taylor Berg-Kirkpatrick Jacob Andreas and Dan Klein. 2014. Unsupervised transcription of piano music. In Advances in neural information processing systems. 1538--1546. Taylor Berg-Kirkpatrick Jacob Andreas and Dan Klein. 2014. Unsupervised transcription of piano music. In Advances in neural information processing systems. 1538--1546.

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