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Maths, Computation and Flamenco: Overview and Challenges

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Mathematics and Computation in Music (MCM 2019)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11502))

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Abstract

Flamenco is a rich performance-oriented art music genre from Southern Spain which attracts a growing community of aficionados around the globe. Due to its improvisational and expressive nature, its unique musical characteristics, and the fact that the genre is largely undocumented, flamenco poses a number of interesting mathematical and computational challenges. Most existing approaches in Musical Information Retrieval (MIR) were developed in the context of popular or classical music and do often not generalize well to non-Western music traditions, in particular when the underlying music theoretical assumptions do not hold for these genres. Over the recent decade, a number of computational problems related to the automatic analysis of flamenco music have been defined and several methods addressing a variety of musical aspects have been proposed. This paper provides an overview of the challenges which arise in the context of computational analysis of flamenco music and outlines an overview of existing approaches.

This research has received funding from the Junta de Andalucía (project P12-TIC-1362), Spanish Ministry of Economy and Competitiveness (project MTM2016-76272-R AEI/FEDER, UE), and the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No. 734922.

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Notes

  1. 1.

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References

  1. Aichholzer, O., Caraballo, L.E., Díaz-Báñez, J.M., Fabila-Monroy, R., Ochoa, C., Nigsch, P.: Characterization of extremal antipodal polygons. Graphs Comb. 31(2), 321–333 (2015)

    Article  MathSciNet  Google Scholar 

  2. Barba, L., Caraballo, L.E., Díaz-Báñez, J.M., Fabila-Monroy, R., Pérez-Castillo, E.: Asymmetric polygons with maximum area. Eur. J. Oper. Res. 248(3), 1123–1131 (2016)

    Article  MathSciNet  Google Scholar 

  3. Bereg, S., Díaz-Báñez, J.M., Kroher, N., Ventura, I.: Computing melodic templates in oral music traditions. Appl. Math. Comput. 44(1), 219–229 (2019)

    MathSciNet  MATH  Google Scholar 

  4. Caraballo, L.E., Díaz-Báñez, J.M., Pérez-Castillo, E.: Finding unknown nodes in phylogenetic graphs. In: Ortuño, F., Rojas, I. (eds.) IWBBIO 2015. LNCS, vol. 9043, pp. 403–414. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-16483-0_40

    Chapter  Google Scholar 

  5. Chemillier, M., Truchet, C.: Computation of words satisfying the rhythmic oddity property (after Simha Arom’s works). Inf. Process. Lett. 86(5), 255–261 (2003)

    Article  MathSciNet  Google Scholar 

  6. COFLA Homepage. http://www.cofla-project.com. Accessed 14 Mar 2019

  7. Díaz-Báñez, J.M.: Mathematics and flamenco: an unexpected partnership. Math. Intell. 39(3), 27–39 (2017)

    Article  MathSciNet  Google Scholar 

  8. Díaz-Báñez, M., Farigu, G., Gómez, F., Rappaport, D., Toussaint, G.T.: El compás flamenco: a phylogenetic analysis. In: Proceedings of BRIDGES: Mathematical Connections in Art, Music and Science, pp. 61–70. Southwestern College, Winfield(2004)

    Google Scholar 

  9. Díaz-Báñez, J.M., Farigu, G., Gómez, F., Rappaport, D., Toussaint, G.T.: Similaridad y evolución en la rtmica del flamenco: una incursión de la matemática computacional. La Gaceta de la Real Sociedad Matemática Española 82, 489–509 (2005)

    Google Scholar 

  10. Díaz-Báñez, J.M., Kroher, N., Rizo, J.: Efficient algorithms for melodic similarity in flamenco singing. In: Proceedings of the 5th International Workshop on Folk Music Analysis (FMA), Paris, France (2015)

    Google Scholar 

  11. Díaz-Báñez, J.M., Rizo, J.C.: An efficient DTW-based approach for melodic similarity in flamenco singing. In: Traina, A.J.M., Traina, C., Cordeiro, R.L.F. (eds.) SISAP 2014. LNCS, vol. 8821, pp. 289–300. Springer, Cham (2014). https://doi.org/10.1007/978-3-319-11988-5_27

    Chapter  Google Scholar 

  12. Gómez, E., Bonada, J.: Towards computer-assisted flamenco transcription: an experimental comparison of automatic transcription algorithms as applied to a cappella singing. Comput. Music J. 37(2), 73–90 (2013)

    Article  Google Scholar 

  13. Gómez, E., Bonada, J., Salamon, J.: Automatic transcription of flamenco singing from monophonic and polyphonic music recordings. In: Proceedings of the III Interdisciplinary Conference on Flamenco Research (INFLA) and II International Workshop of Folk Music Analysis (FMA), Seville, Spain (2012)

    Google Scholar 

  14. Guastavino, C., Gómez, F., Toussaint, G., Marandola, F., Gómez, E.: Measuring similarity between flamenco rhythmic patterns. J. New Music Res. 38(2), 129–138 (2009)

    Article  Google Scholar 

  15. Han, Y., Kim, J., Lee, K., Han, Y., Kim, J., Lee, K.: Deep convolutional neural networks for predominant instrument recognition in polyphonic music. IEEE/ACM Trans. Audio Speech Lang. Process. 25(1), 208–221 (2017)

    Article  Google Scholar 

  16. Kroher, N.: Flamenco music information retrieval. Ph.D. thesis, Universidad de Sevilla (2018)

    Google Scholar 

  17. Kroher, N., Díaz-Báñez, J.M.: Audio-based melody categorisation: exploring signal representations and evaluation strategies. Comput. Music J. 41(4), 1–19 (2017)

    Google Scholar 

  18. Kroher, N., Díaz-Báñez, J.M., Mora, J., Gómez, E.: Corpus COFLA: a research corpus for the computational study of flamenco music. J. Comput. Cult. Herit. 9(2), 10–21 (2016)

    Article  Google Scholar 

  19. Kroher, N., Díaz-Báñez, J.M.: Modelling melodic variation and extracting melodic templates from flamenco singing performances. J. Math. Music (2019, to appear)

    Google Scholar 

  20. Kroher, N., Pikrakis, A., Moreno, J., Díaz-Báñez, J.M.: Discovery of repeated vocal patterns in polyphonic audio: a case study on flamenco music. In: Proceedings of 23rd European Signal Processing Conference (EUSIPCO), Nice, France, pp. 41–45. IEEE (2015)

    Google Scholar 

  21. Kroher, N., Pikrakis, A., Díaz-Báñez, J.M.: Discovery of repeated melodic phrases in folk singing recordings. IEEE Trans. Multimed. 20(6), 1291–1304 (2018)

    Article  Google Scholar 

  22. Kroher, N., Gómez, E.: Automatic transcription of flamenco singing from polyphonic music recordings. IEEE Trans. Audio Speech Lang. Process. 24(5), 901–913 (2016)

    Article  Google Scholar 

  23. Montiel, M., Peck, R.W.: Mathematical Music Theory: Algebraic, Geometric, Combinatorial, Topological and Applied Approaches to Understanding Musical Phenomena. World Scientific Publishing, London (2018)

    Book  Google Scholar 

  24. Mora, J., Gómez, F., Gómez, E., Díaz-Báñez, J.M.: Melodic contour and mid-level global features applied to the analysis of flamenco cantes. J. New Music Res. 45(2), 145–159 (2016)

    Article  Google Scholar 

  25. Mora, J., Gómez, F., Gómez, E., Escobar, F.J., Díaz-Báñez, J.M.: Characterization and melodic similarity of a cappella flamenco cantes. In: Proceedings of the 11th Conference of the International Society for Music Information (ISMIR), Utrecht, Holland (2010)

    Google Scholar 

  26. Oramas, S., Gómez, F., Gómez, E., Mora, J.: FlaBase: towards the creation of a flamenco music knowledge base. In: Proceedings 16th International Society for Music Information Retrieval Conference (ISMIR), Málaga, Spain (2015)

    Google Scholar 

  27. Pikrakis, A., et al.: Tracking melodic patterns in flamenco singing by analyzing polyphonic recordings. In: Proceedings of the 13th Conference of the International Society for Music Information Retrieval, ISMIR, Porto, Portugal (2012)

    Google Scholar 

  28. Pikrakis, A., Kroher, N., Díaz-Báñez, J.M.: Detection of melodic patterns in automatic flamenco transcriptions. In: Proceedings of the 6th International Workshop on Folk Music Analysis (FMA), pp. 14–17 (2016)

    Google Scholar 

  29. Schluter, J., Bock, S.: Improved musical onset detection with convolutional neural networks. In: IEEE International Conference on Acoustics, Speech and Signal Processing ICASSP, Florence, Italy, pp. 6979–6983 (2014)

    Google Scholar 

  30. Van den Oord, A., Dieleman, S., Schrauwen, B.: Deep content-based music recommendation. In: Advances in Neural Information Processing Systems (NIPS), pp. 2643–2651 (2013)

    Google Scholar 

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Author information

Authors and Affiliations

  1. Departamento de Matemática Aplicada II, Universidad de Sevilla, Seville, Spain

    José-Miguel Díaz-Báñez

  2. MXX, London, UK

    Nadine Kroher

Authors
  1. José-Miguel Díaz-Báñez
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  2. Nadine Kroher
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Correspondence to José-Miguel Díaz-Báñez .

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Editors and Affiliations

  1. Georgia State University, Atlanta, GA, USA

    Mariana Montiel

  2. Technical University of Madrid, Madrid, Spain

    Francisco Gomez-Martin

  3. Technological University of the Mixteca, Oaxaca, Mexico

    Octavio A. Agustín-Aquino

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Díaz-Báñez, JM., Kroher, N. (2019). Maths, Computation and Flamenco: Overview and Challenges. In: Montiel, M., Gomez-Martin, F., Agustín-Aquino, O.A. (eds) Mathematics and Computation in Music. MCM 2019. Lecture Notes in Computer Science(), vol 11502. Springer, Cham. https://doi.org/10.1007/978-3-030-21392-3_29

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  • DOI: https://doi.org/10.1007/978-3-030-21392-3_29

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  • Online ISBN: 978-3-030-21392-3

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