Improving audio chord transcription by exploiting harmonic and metric knowledge

Proceedings of the 13th International Society for Music Information Retrieval Conference, ISMIR 2012

Volumn , Issue , 2012, Pages 295-300

  De Haas, W Bas ^a   Magalhães, José Pedro ^b   Wiering, Frans ^a  

^a UTRECHT UNIVERSITY   (Netherlands)

^b UNIVERSITY OF OXFORD   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

AUDIO SOURCES; BEST MATCH; DOMAIN-SPECIFIC KNOWLEDGE; MUSICAL AUDIO; PLUGIN ARCHITECTURE; SPECTRAL FEATURE; THEORETICAL MODELS;

INFORMATION RETRIEVAL; TRANSCRIPTION;

AUDIO ACOUSTICS;

EID: 84873462428     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (15)

1. J.P. Bello and J. Pickens. A robust mid-level representation for harmonic content in music signals. In ISMIR Proceedings, pages 304-311, 2005.
2. M.E.P. Davies and M.D. Plumbley. Context-dependent beat tracking of musical audio. Audio, Speech, and Language Processing, IEEE Transactions on, 15(3):1009-1020, 2007.
3. T. Fujishima. Realtime chord recognition of musical sound: A system using common Lisp music. In ISMIR Proceedings, pages 464-467, 1999.
4. W.B. de Haas. Music information retrieval based on tonal harmony. PhD thesis, Utrecht University, 2012.
5. W.B. de Haas, J.P. Magalhães, F. Wiering, and R.C. Veltkamp. HarmTrace: Improving harmonic similarity estimation using functional harmony analysis. In ISMIR Proceedings, 2011.
6. W.B. de Haas and F. Wiering. Hooked on music information retrieval. Empirical Musicology Review, 5(4):176-185, 2010.
7. C.L. Krumhansl. Cognitive Foundations of Musical Pitch. Oxford University Press, USA, 2001.
8. J. P. Magalhães and W. B. de Haas. Functional Modelling of Musical Harmony - an Experience Report. In Proceedings of the International Conference on Functional Programming, pages 156-162, 2011.
9. M. Mauch. Automatic chord transcription from audio using computational models of musical context. PhD thesis, Queen Mary University of London, 2010.
10. M. Mauch, C. Cannam, M. Davies, S. Dixon, C. Harte, S. Kolozali, D. Tidhar, and M. Sandler. Omras2 metadata project 2009. In ISMIR Proceedings, 2009.
11. M. Mauch and S. Dixon. Approximate note transcription for the improved identification of difficult chords. In ISMIR Proceedings, pages 135-140, 2010.
12. Y. Ni, M. McVicar, R. Santos-Rodriguez, and T. De Bie. An end-to-end machine learning system for harmonic analysis of music. Audio, Speech, and Language Processing, IEEE Transactions on, 20(6):1771-1783, 2012.
13. M. Rohrmeier. Towards a generative syntax of tonal harmony. Journal of Mathematics and Music, 5(1):35-53, 2011.
14. D. Temperley. The Cognition of Basic Musical Structures. Cambridge, MA, MIT Press, 2001.
15. G.H. Wakefield. Mathematical representation of joint timechroma distributions. In Conference on Advanced Signal Processing Algorithms, Architectures, and Implementations, pages 637-645, 1999.