References
- 1Aldwell, E., Schachter, C., & Cadwallader, A. (2011). Harmony and Voice Leading. Schirmer, 4th edition.
- 2Baeza-Yates, R. A., & Ribeiro-Neto, B. (1999). Modern Information Retrieval. Addison-Wesley Longman Publishing Co., Inc., Boston, MA, USA.
- 3Barthelemy, J., & Bonardi, A. (2001). Figured bass and tonality recognition. In: International Symposium on Music Information Retrieval (ISMIR).
- 4Collins, M. (2002). Discriminative training methods for hidden Markov models: Theory and experiments with perceptron algorithms. In: Proceedings of the ACL-02 Conference on Empirical Methods in Natural Language Processing, EMNLP ’02, 1–8.
ACL , Stroudsburg, PA, USA. DOI: 10.3115/1118693.1118694 - 5Cormen, T. H., Leiserson, C. E., Rivest, R. L., & Stein, C. (2009). Introduction to Algorithms, Third Edition. The MIT Press, 3rd edition.
- 6Devaney, J., Arthur, C., Condit-Schultz, N., & Nisula, K. (2015). Theme and variation encodings with roman numerals (TAVERN): A new data set for symbolic music analysis. In: International Society for Music Information Retrieval Conference (ISMIR).
- 7Gómez, E. (2006). Tonal Description of Music Audio Signals. PhD thesis, Universitat Pompeu Fabra.
- 8Graves, A. (2012). Supervised Sequence Labelling with Recurrent Neural Networks, volume 385 of Studies in Computational Intelligence. Springer. DOI: 10.1007/978-3-642-24797-2
- 9Harte, C. (2010). Towards Automatic Extraction of Harmony Information from Music Signals. PhD thesis, Queen Mary University of London.
- 10Jaques, N., Gu, S., Bahdanau, D., Hernández-Lobato, J. M., Turner, R. E., & Eck, D. (2017). Sequence tutor: Conservative fine-tuning of sequence generation models with kl-control. In: Proceedings of the 34th International Conference on Machine Learning, (ICML), 1645–1654. Sydney, Australia.
- 11Kong, L., Dyer, C., & Smith, N. A. (2016). Segmental recurrent neural networks. In: International Conference on Learning Representations (ICLR). San Juan, Puerto Rico.
- 12Kostka, S., & Payne, D. (1984). Tonal Harmony. McGraw-Hill.
- 13Kschischang, F. R., Frey, B., & Loeliger, H.-A. (2001). Factor graphs and the sum-product algorithm. IEEE Transactions on Information Theory, 47(2), 498–519. DOI: 10.1109/18.910572
- 14Lafferty, J., McCallum, A., & Pereira, F. (2001). Conditional random fields: Probabilistic models for segmenting and labeling sequence data. In: Proceedings of the 18th International Conference on Machine Learning, 282–289. Williamstown, MA.
- 15Maxwell, H. J. (1992).
An expert system for harmonizing analysis of tonal music . In: Balaban, M., Ebcioğlu, K., & Laske, O. (eds.), Understanding Music with AI, pages 334–353. MIT Press, Cambridge, MA, USA. - 16Muis, A. O., & Lu, W. (2016). Weak semi-Markov CRFs for noun phrase chunking in informal text. In: Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 714–719.
Association for Computational Linguistics , San Diego, California. DOI: 10.18653/v1/N16-1085 - 17Papadopoulos, H., & Peeters, G. (2009). Local key estimation based on harmonic and metric structures. In: International Conference on Digital Audio Effects (DAFx-09).
- 18Pardo, B., & Birmingham, W. P. (2002). Algorithms for chordal analysis. Computer Music Journal, 26(2), 27–49. DOI: 10.1162/014892602760137167
- 19Rabiner, L. R. (1989). A tutorial on hidden Markov models and selected applications in speech recognition. Proceedings of the IEEE, 77(2), 257–286. DOI: 10.1109/5.18626
- 20Radicioni, D. P., & Esposito, R. (2010).
BREVE: an HMPerceptron-based chord recognition system . In: Advances in Music Information Retrieval, 143–164. Springer, Berlin, Heidelberg. DOI: 10.1007/978-3-642-11674-2_7 - 21Raphael, C., & Stoddard, J. (2003). Harmonic analysis with probabilistic graphical models. In: International Conference on Music Information Retrieval (ISMIR).
- 22Rizo, D., Illescas, P. R., & Iñesta, J. M. (2016).
Interactive melodic analysis . In: Meredith, D. (ed.), Computational Music Analysis, 191–219. Springer International Publishing, Cham. DOI: 10.1007/978-3-319-25931-4_8 - 23Rocher, T., Robine, M., Hanna, P., & Strandh, R. (2009). Dynamic chord analysis for symbolic music. In: International Computer Music Conference (ICMC).
- 24Sarawagi, S., & Cohen, W. W. (2004). Semi-Markov conditional random fields for information extraction. In: Proceedings of the 17th International Conference on Neural Information Processing Systems (NIPS’04), 1185–1192.
MIT Press , Cambridge, MA, USA. - 25Scholz, R., & Ramalho, G. (2008). Cochonut: Recognizing complex chords from MIDI guitar sequences. In: International Conference on Music Information Retrieval (ISMIR), 27–32. Philadelphia, USA.
- 26Temperley, D., & Sleator, D. (1999). Modeling meter and harmony: A preference-rule approach. Computer Music Journal, 23(1), 10–27. DOI: 10.1162/014892699559616
- 27Tsochantaridis, I., Hofmann, T., Joachims, T., & Altun, Y. (2004). Support vector machine learning for interdependent and structured output spaces. In: Proceedings of the Twenty-first International Conference on Machine Learning (ICML’04), 104–111.
ACM , New York, NY, USA. DOI: 10.1145/1015330.1015341 - 28Winograd, T. (1968). Linguistics and the computer analysis of tonal harmony. Journal of Music Theory, 12(1), 2–49. DOI: 10.2307/842885