Augmented Study Room: Computer Support for Technical and Perceptual Development of Musical Performance
Abstract
This paper presents a proposal for the use of computational tools for the acoustical analysis of recorded musical sound content in teaching and learning environments as a support for the technical and perceptive development in music performance. The methodology was tested by means of a research carried out during two semesters with an undergraduate class of clarinet students. We describe the implementation of the proposed “augmented study room” as a university level music learning tool.
Keywords:
Augmented Study Room, Musical Performance, Music Learning
References
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Campolina, T., Loureiro, M., and Mota, D. (2009). Expan: a tool for musical expressiveness analysis. Proceedings of the 2nd International Conference of Students of Systematic Musicology, pages 24–27.
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Flavell, J. H. (1979). Metacognition and Cognitive Monitoring: A New Area of Cognitive-Developmental Inquiry. American Psychologist, 34(10):906–911.
Freitas, S. G. A. d. (2013). Modelagem como estratégia para o desenvolvimento de recursos expressivos na performance pianistica: três estudos de casos.
Gerling, C. C. and Freitas, S. (2016). Reflexões sobre a modelagem como estratégia deestudo: relatos de duas investigações com estudantes de graduação e pós-graduação. Arteriais-Revista do Programa de Pós-Gradução em Artes, 1(1):90–106.
Krasner, G. E., Pope, S. T., et al. (1988). A description of the model-view-controller user interface paradigm in the smalltalk-80 system. Journal of object oriented programming, 1(3):26–49.
Loureiro, M., Magalhães, T., et al. (2008). Segmentação e extração de descritores de expressividade em sinais musicais monofônicos. Seminário Música Ciência Tecnologia,1(3).
Marzano, R. J. e. a. (1988). Dimensions of thinking: A framework for curriculum and instruction. ERIC.
Mauch, M. and Dixon, S. (2014). pyin: A fundamental frequency estimator using probabilistic threshold distributions. In 2014 IEEE International Conference on Acoustics,Speech and Signal Processing (ICASSP), pages 659–663. IEEE.
Schedl, M., Gómez, E., Urbano, J., et al. (2014). Music information retrieval: Recent developments and applications. Foundations and Trends in Information Retrieval, 8(2-3):127–261.
Schmidt, R. A. and Lee, T. (1988). Motor control and learning. Human kinetics.
Campolina, T., Loureiro, M., and Mota, D. (2009). Expan: a tool for musical expressiveness analysis. Proceedings of the 2nd International Conference of Students of Systematic Musicology, pages 24–27.
Downie, J. S. (2003). Music information retrieval. Annual review of information scienceand technology, 37(1):295–340.
Flavell, J. H. (1979). Metacognition and Cognitive Monitoring: A New Area of Cognitive-Developmental Inquiry. American Psychologist, 34(10):906–911.
Freitas, S. G. A. d. (2013). Modelagem como estratégia para o desenvolvimento de recursos expressivos na performance pianistica: três estudos de casos.
Gerling, C. C. and Freitas, S. (2016). Reflexões sobre a modelagem como estratégia deestudo: relatos de duas investigações com estudantes de graduação e pós-graduação. Arteriais-Revista do Programa de Pós-Gradução em Artes, 1(1):90–106.
Krasner, G. E., Pope, S. T., et al. (1988). A description of the model-view-controller user interface paradigm in the smalltalk-80 system. Journal of object oriented programming, 1(3):26–49.
Loureiro, M., Magalhães, T., et al. (2008). Segmentação e extração de descritores de expressividade em sinais musicais monofônicos. Seminário Música Ciência Tecnologia,1(3).
Marzano, R. J. e. a. (1988). Dimensions of thinking: A framework for curriculum and instruction. ERIC.
Mauch, M. and Dixon, S. (2014). pyin: A fundamental frequency estimator using probabilistic threshold distributions. In 2014 IEEE International Conference on Acoustics,Speech and Signal Processing (ICASSP), pages 659–663. IEEE.
Schedl, M., Gómez, E., Urbano, J., et al. (2014). Music information retrieval: Recent developments and applications. Foundations and Trends in Information Retrieval, 8(2-3):127–261.
Schmidt, R. A. and Lee, T. (1988). Motor control and learning. Human kinetics.
Published
2020-11-24
How to Cite
OLIVEIRA NETO, Aluizio B.; LOUREIRO, Maurício Alves.
Augmented Study Room: Computer Support for Technical and Perceptual Development of Musical Performance. In: BRAZILIAN SYMPOSIUM ON COMPUTERS IN EDUCATION (SBIE), 31. , 2020, Online.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2020
.
p. 162-171.
DOI: https://doi.org/10.5753/cbie.sbie.2020.162.
