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MTD: A Multimodal Dataset of Musical Themes for MIR Research Cover

MTD: A Multimodal Dataset of Musical Themes for MIR Research

Transactions of the International Society for Music Information Retrieval
Volume 3 (2020): Issue 1
By: Frank Zalkow,  Stefan Balke,  Vlora Arifi-Müller and  Meinard Müller  
Open Access
|Oct 2020

References

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  62. 62Zalkow, F., Balke, S., & Müller, M. (2019). Evaluating salience representations for cross-modal retrieval of Western classical music recordings. In Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), pages 331–335. Brighton, United Kingdom. DOI: 10.1109/ICASSP.2019.8683609
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  63. 63Zalkow, F., & Müller, M. (2020). Using weakly aligned score-audio pairs to train deep chroma models for cross-modal music retrieval. In Proceedings of the International Society for Music Information Retrieval Conference (ISMIR), pages 184–191. Montréal, Canada.
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DOI: https://doi.org/10.5334/tismir.68 | Journal eISSN: 2514-3298
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Language: English
Submitted on: Jul 23, 2020
Accepted on: Sep 21, 2020
Published on: Oct 21, 2020
Published by: Ubiquity Press
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year
Keywords:
Musical Themes,
Western Classical Music,
Sheet Music,
Audio,
MIDI,
Score-Audio Alignments

© 2020 Frank Zalkow, Stefan Balke, Vlora Arifi-Müller, Meinard Müller, published by Ubiquity Press
This work is licensed under the Creative Commons Attribution 4.0 License.

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