References
- 1Bay, M., Bello, J. P., Burgoyne, J. A., Chew, E., Ehmann, A. F., Khadkevich, M., Mauch, M., McVicar, M., Pauwels, J., and Rocher, T. (2010). The Utrecht agreement on chord evaluation.
https://www.music-ir.org/mirex/wiki/The_Utrecht_Agreement_on_Chord_Evaluation . Accessed: 2020-08-13. - 2Burred, J. J., and Lerch, A. (2004). Hierarchical automatic audio signal classification. Journal of the Audio Engineering Society, 52(7/8): 724–739.
- 3Carsault, T., Nika, J., and Esling, P. (2018). Using musical relationships between chord labels in automatic chord extraction tasks. In Proceedings of the 19th International Society for Music Information Retrieval Conference.
- 4Dannenberg, R. B., and Goto, M. (2008).
Music structure analysis from acoustic signals . In Handbook of Signal Processing in Acoustics, pages 305–331. Springer. DOI: 10.1007/978-0-387-30441-0_21 - 5Essid, S., Richard, G., and David, B. (2005). Instrument recognition in polyphonic music based on automatic taxonomies. IEEE Transactions on Audio, Speech, and Language Processing, 14(1): 68–80. DOI: 10.1109/TSA.2005.860351
- 6Harte, C. (2010). Towards automatic extraction of harmony information from music signals. PhD thesis, Queen Mary University of London.
- 7Harte, C., Sandler, M. B., Abdallah, S. A., and Gómez, E. (2005). Symbolic representation of musical chords: A proposed syntax for text annotations. In Proceedings of the 6th International Conference on Music Information Retrieval (ISMIR), pages 66–71.
- 8Huber, P. J. (1981). Robust Statistics. John Wiley & Sons, New York. DOI: 10.1002/0471725250
- 9Humphrey, E., and Bello, J. (2015). Four timely insights on automatic chord estimation. In Müller, M. and Wiering, F., editors, Proceedings of the 16th International Society for Music Information Retrieval Conference, pages 673–679.
- 10Lewishon, M. (1988). The Complete Beatles Recording Sessions: The Official Story of the Abbey Road Years 1962—1970. Bounty Books, London.
- 11Mauch, M. (2010). Automatic chord transcription from audio using computational models of musical context. PhD thesis, Queen Mary University of London.
- 12McFee, B., and Bello, J. (2017). Structured training for large-vocabulary chord recognition. In Proceedings of the 18th International Society for Music Information Retrieval Conference.
- 13McFee, B., and Kinnaird, K. M. (2019). Improving structure evaluation through automatic hierarchy expansion. In Proceedings of the 20th International Society for Music Information Retrieval Conference, pages 152–158.
- 14McFee, B., Nieto, O., Farbood, M. M., and Bello, J. P. (2017). Evaluating hierarchical structure in music annotations. Frontiers in Psychology, 8: 1337. DOI: 10.3389/fpsyg.2017.01337
- 15McGuirl, M. R., Kinnaird, K. M., Savard, C., and Bugbee, E. H. (2018). SE and SNL diagrams: Flexible data structures for MIR. In Proceedings of the 19th International Society for Music Information Retrieval Conference, pages 341–347.
- 16Nieto, O., and Bello, J. P. (2016). Systematic exploration of computational music structure research. In Proceedings of the 17th International Society for Music Information Retrieval Conference, pages 547–553.
- 17Paulus, J. (2010). Improving Markov model based music piece structure labelling with acoustic information. In Proceedings of the 11th International Society for Music Information Retrieval Conference, pages 303–308.
- 18Paulus, J., and Klapuri, A. (2006). Music structure analysis by finding repeated parts. In Proceedings of the 1st ACM Workshop on Audio and Music Computing Multimedia, pages 59–68.
ACM . DOI: 10.1145/1178723.1178733 - 19Paulus, J., Müller, M., and Klapuri, A. (2010). State of the art report: Audio-based music structure analysis. In Proceedings of the 11th International Society for Music Information Retrieval Conference, pages 625–636.
- 20Pauwels, J., O’Hanlon, K., Gómez, E., and Sandler, M. B. (2019). 20 years of automatic chord recognition from audio. In Proceedings of the 20th International Society for Music Information Retrieval Conference, pages 54–63.
- 21Pauwels, J., and Peeters, G. (2013). Evaluating automatically estimated chord sequences. In 2013 IEEE International Conference on Acoustics, Speech and Signal Processing, pages 749–753.
IEEE . DOI: 10.1109/ICASSP.2013.6637748 - 22Pollack, A. W. (2000). ‘notes on …’ series.
https://www.recmusicbeatles.com/public/files/awp/awp.html , accessed 2020-08-31. - 23Raffel, C., McFee, B., Humphrey, E. J., Salamon, J., Nieto, O., Liang, D., and Ellis, D. P. W. (2014). Mir_eval: A transparent implementation of common MIR metrics. In Proceedings of the 15th International Society for Music Information Retrieval Conference, pages 367–372.
- 24Seabold, S., and Perktold, J. (2010). statsmodels: Econometric and statistical modeling with python. In 9th Python in Science Conference. DOI: 10.25080/Majora-92bf1922-011
- 25Smith, J. B. L., Burgoyne, J. A., Fujinaga, I., De Roure, D., and Downie, J. S. (2011). Design and creation of a large-scale database of structural annotations. In Proceedings of the 12th International Society for Music Information Retrieval Conference, pages 555–560.
- 26Ullrich, K., Schlüter, J., and Grill, T. (2014). Boundary detection in music structure analysis using convolutional neural networks. In Proceedings of the 15th International Society for Music Information Retrieval Conference, pages 417–422.
