References
- Achankunju, S. P. (2018). Music search engine from noisy OMR data. In International Workshop on Reading Music Systems, pages 23–24.
- Babenko, A., and Lempitsky, V. (2015). Aggregating local deep features for image retrieval. In Proceedings of the IEEE International Conference on Computer Vision, pages 1269–1297. DOI: 10.1109/ICCV.2015.150
- Calvo-Zaragoza, J., Hajič, J.,
Jr. and Pacha, A. (2020). Understanding optical music recognition. ACM Computing Surveys (CSUR), 53(4): 1–35. DOI: 10.1145/3397499 - Calvo-Zaragoza, J., Toselli, A. H., and Vidal, E. (2018). Probabilistic music-symbol spotting in handwritten scores. In IEEE International Conference on Frontiers in Handwriting Recognition, pages 558–563. DOI: 10.1109/ICFHR-2018.2018.00103
- Damm, D., Fremerey, C., Kurth, F., Müller, M., and Clausen, M. (2008). Multimodal presentation and browsing of music. In Proceedings of the International Conference on Multimodal Interfaces, pages 205–208. DOI: 10.1145/1452392.1452436
- Dorfer, M., Arzt, A., and Widmer, G. (2016). Towards score following in sheet music images. In Proceedings of the International Society for Music Information Retrieval Conference, pages 789–795.
- Dorfer, M., Arzt, A., and Widmer, G. (2017). Learning audio-sheet music correspondences for score identification and offline alignment. In Proceedings of the International Society for Music Information Retrieval Conference, pages 115–122.
- Dorfer, M., Hajič, J.,
Jr. , Arzt, A., Frostel, H., and Widmer, G. (2018a). Learning audio-sheet music correspondences for cross-modal retrieval and piece identification. Transactions of the International Society for Music Information Retrieval, 1(1): 22–33. DOI: 10.5334/tismir.12 - Dorfer, M., Henkel, F., and Widmer, G. (2018b). Learning to listen, read, and follow: Score following as a reinforcement learning game. In Proceedings of the International Society for Music Information Retrieval Conference, pages 784–791.
- Dorfer, M., Schlüter, J., Vall, A., Korzeniowski, F., and Widmer, G. (2018c). End-to-end crossmodality retrieval with CCA projections and pairwise ranking loss. International Journal of Multimedia Information Retrieval, 7(2): 117–128. DOI: 10.1007/s13735-018-0151-5
- Fremerey, C., Clausen, M., Ewert, S., and Müller, M. (2009). Sheet music-audio identification. In Proceedings of the International Society for Music Information Retrieval Conference, pages 645–650.
- Fremerey, C., Müller, M., and Clausen, M. (2010). Handling repeats and jumps in score-performance synchronization. In Proceedings of the International Society for Music Information Retrieval Conference, pages 243–248.
- Fremerey, C., Müller, M., Kurth, F., and Clausen, M. (2008). Automatic mapping of scanned sheet music to audio recordings. In Proceedings of the International Conference on Music Information Retrieval, pages 413–418.
- Hajič, J., Kolárová, M., Pacha, A., and Calvo-Zaragoza, J. (2018). How current optical music recognition systems are becoming useful for digital libraries. In Proceedings of the 5th International Conference on Digital Libraries for Musicology, pages 57–61. DOI: 10.1145/3273024.3273034
- Henkel, F., Balke, S., Dorfer, M., and Widmer, G. (2019). Score following as a multimodal reinforcement learning problem. Transactions of the International Society for Music Information Retrieval, 2(1): 67–81. DOI: 10.5334/tismir.31
- Izmirli, Ö., and Sharma, G. (2012). Bridging printed music and audio through alignment using a midlevel score representation. In Proceedings of the International Society for Music Information Retrieval Conference, pages 61–66.
- Kurth, F., Müller, M., Fremerey, C., Chang, Y.-H., and Clausen, M. (2007). Automated synchronization of scanned sheet music with audio recordings. In Proceedings of the International Conference on Music Information Retrieval, pages 261–266.
- Malik, R., Roy, P. P., Pal, U., and Kimura, F. (2013). Handwritten musical document retrieval using music-score spotting. In IEEE International Conference on Document Analysis and Recognition, pages 832–836. DOI: 10.1109/ICDAR.2013.170
- Radenovic, F., Tolias, G., and Chum, O. (2016). CNN image retrieval learns from BoW: Unsupervised fine-tuning with hard examples. In Proceedings of the European Conference on Computer Vision, pages 3–20. DOI: 10.1007/978-3-319-46448-0_1
- Radenovic, F., Tolias, G., and Chum, O. (2018). Finetuning CNN image retrieval with no human annotation. IEEE Transactions on Pattern Analysis and Machine Intelligence, 41(7): 1655–1668. DOI: 10.1109/TPAMI.2018.2846566
- Raffel, C. (2016). Learning-Based Methods for Comparing Sequences, with Applications to Audio-to-MIDI Alignment and Matching. PhD thesis, Columbia University. DOI: 10.1109/ICASSP.2016.7471641
- Shan, M., and Tsai, T. (2020). Improved handling of repeats and jumps in audio-sheet image synchronization. In Proceedings of the International Society for Music Information Retrieval Conference, pages 62–69.
- Tanprasert, T., Jenrungrot, T., Müller, M., and Tsai, T. (2019). MIDI-sheet music alignment using bootleg score synthesis. In Proceedings of the International Society for Music Information Retrieval Conference, pages 91–98.
- Thomas, V., Fremerey, C., Müller, M., and Clausen, M. (2016).
Linking sheet music and audio – challenges and new approaches . In Müller, M., Goto, M., and Schedl, M., editors, Dagstuhl Follow-Ups, 3: 1–22. Schloss Dagstuhl–Leibniz-Zentrum für Informatik, Dagstuhl, Germany. DOI: 10.4230/dfu.vol3.11041.1 - Thompson, J., Hankinson, A., and Fujinaga, I. (2011). Searching the liber usualis: Using CouchDB and ElasticSearch to query graphical music documents. In Proceedings of the International Society for Music Information Retrieval Conference.
- Tolias, G., Sicre, R., and Jégou, H. (2016). Particular object retrieval with integral max-pooling of CNN activations. In Proceedings of the International Conference on Learning Representations.
- Tsai, T. (2020). Towards linking the Lakh and IMSLP datasets. In Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing, pages 546–550. DOI: 10.1109/ICASSP40776.2020.9053815
- Tsai, T., Yang, D., Shan, M., Tanprasert, T., and Jenrungrot, T. (2020). Using cell phone pictures of sheet music to retrieve MIDI passages. IEEE Transactions on Multimedia. DOI: 10.1109/TMM.2020.2973831
- Wang, A. (2003). An industrial strength audio search algorithm. In Proceedings of the International Conference on Music Information Retrieval, pages 7–13.
- Yang, D., Tanprasert, T., Jenrungrot, T., Shan, M., and Tsai, T. (2019). MIDI passage retrieval using cell phone pictures of sheet music. In Proceedings of the International Society for Music Information Retrieval Conference, pages 916–923.
- Yang, D., and Tsai, T. (2020). Camera-based piano sheet music identification. In Proceedings of the International Society for Music Information Retrieval Conference, pages 481–488.
DOI: https://doi.org/10.5334/tismir.70 | Journal eISSN: 2514-3298
Language: English
Submitted on: Aug 29, 2020
Accepted on: Jan 23, 2021
Published on: Apr 1, 2021
Published by: Ubiquity Press
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year
Keywords:
© 2021 Daniel Yang, T. J. Tsai, published by Ubiquity Press
This work is licensed under the Creative Commons Attribution 4.0 License.
