Araştırma Makalesi
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A Comparative Study of Rhythmic Complexity Measures in Music Performance

Yıl 2024, Cilt: 11 Sayı: 2, 478 - 487, 25.12.2024
https://doi.org/10.26650/CONS2024-1562373

Öz

The study of rhythmic complexity aims to determine the perceptual complexity of rhythms and how easily they can be remembered and performed. This research report evaluates two preliminary studies that approached rhythmic complexity from two complementary perspectives: conceptual understanding and performance. The research focuses on five rhythmic complexity measures: Lempel-Ziv, Keith, Tanguiane, Weighted Note-to-Beat Distance (WNBD), and Pressing. The rhythms used in the studies were created by the algorithmic software designed based on the conservatory entrance exam questions. In the first study, three expert raters evaluated the suitability and difficulty of 80 patterns. Their scores were compared with the values obtained from the complexity scales. The second study involved 11 conservatory students (5 female, 6 male) performing 16 selected rhythms from the initial pool.
The results demonstrated varying degrees of alignment between different scales and expert predictions under different conditions. In fırst study, Pressing, WNBD, Keith and Tanguiane complexity scales were found to be consistent with expert raters. In the second study, the expert raters provided the most accurate predictions for rhythm repetition difficulty, followed by the WNBD scale and the Tanguiane scale. In addition, there was a significant negative correlation between the average time spent and performance scores.

Etik Beyan

Publication Ethics Committee for Science and Engineering Sciences Tel +90 232 260 1001 (pbx) Faks: +90 232 260 1004 e-mail: iletisim@idu.edu.tr Ethical approval document information Protocol No: 2022/04 Acceptance Date: 18/11//2022 Decision Number: 2022/09-01 Place: Izmir Democracy University

Destekleyen Kurum

Bu çalışma TÜBİTAK 1001 - Bilimsel Ve Teknolojik Araştırma Projelerini Destekleme Programı kapsamında “Çevrimiçi Müzik Eğitiminde Kullanılma Amaçlı Öğrenci Müzik Egzersiz İcrası Otomatik Notlandırma Sistemi Tasarımı” başlıklı, 121E198 numaralı proje içinde gerçekleştirilmiştir.

Proje Numarası

121E198

Kaynakça

  • Arom, S., & Ligeti, G. (1991). African Polyphony and Polyrhythm. (No Title). https://doi.org/10.1017/cbo9780511518317 google scholar
  • Baysal, O., & Bozkurt, B. (2022). MAST rhythm dataset [Data set]. Zenodo. https://doi.org/10.5281/zenodo.7243752 google scholar
  • Bolton, T. L. (1894). Rhythm. The American Journal of Psychology, 6(2), 145. https://doi.org/10.2307/1410948 google scholar
  • Buffardi, L. (1971). Factors affecting the filled-duration illusion in the auditory, tactual, and visual modalities. Perception & Psychophysics, 10(4), 292-294. https://doi.org/10.3758/bf03212828 google scholar
  • Clarke, E. F. (1987). Levels of structure in the organization of musical time. Contemporary Music Review, 2(1), 211-238. https://doi.org/10. 1080/07494468708567059 google scholar
  • de Fleurian, R., Blackwell, T., Ben-Tal, O., & Müllensiefen, D. (2016). Information-Theoretic Measures Predict the Human Judgment of Rhythm Complexity. Cognitive Science, 41(3), 800-813. https://doi.org/10.1111/cogs.12347 google scholar
  • Essens, P. (1995). Structuring temporal sequences: Comparison of models and factors of complexity. Perception & Psychophysics, 57(4), 519-532. https://doi.org/10.3758/bf03213077 google scholar
  • Fraisse, P. (1956). Fraisse (Paul). — Les Structures Rythmiques. Etude psychologique, Erasme, 1956, Bruxelles-Paris. Bulletin de Psychologie, 13(177), 655-657. https://www.persee.fr/doc/bupsy_0007-4403_1960_num_13_177_8359_t1_0655_0000_1 google scholar
  • Fraisse, P. (1982). Rhythm and Tempo. Psychology of Music, 1(1), 149-180. https://doi.org/10.1016/b978-0-12-213562-0.50010-3 google scholar
  • Gomez, F., Melvin, A., Rappaport, D., & Toussaint, G. (n.d.). Mathematical Measures of Syncopation. Retrieved January 31, 2024, from https://research.cs.queensu.ca/home/daver/Pubs/MyPDF/MeasureSycopa.pdf google scholar
  • Keith, M. (1991). From Polychords to Polya: Adventures in Musical Combinatorics. Vinculum Press. google scholar
  • Lempel, A., & Ziv, J. (1976). On the Complexity of Finite Sequences. IEEE Transactions on Information Theory, 22(1), 75-81. https: //doi.org/10.1109/tit.1976.1055501 google scholar
  • Lerdahl, F., & Jackendoff, R. S. (1996). A Generative Theory of Tonal Music, reissue, with a new preface. MIT Press. google scholar
  • Longuet-Higgins, H. C., & Lee, C. S. (1984). The Rhythmic Interpretation of Monophonic Music. Music Perception: An Interdisciplinary Journal, 1(4), 424-441. https://doi.org/10.2307/40285271 google scholar
  • Povel, D.-J. (1981). Internal representation of simple temporal patterns. Journal of Experimental Psychology: Human Perception and Perfor-mance, 7(1), 3-18. https://doi.org/10.1037/0096-1523.7.1.3 google scholar
  • Povel, D.-J. (1984). A theoretical framework for rhythm perception. Psychological Research, 45(4), 315-337. https://doi.org/10.1007/bf00309709 google scholar
  • Povel, D.-J., & Essens, P. (1985). Perception of Temporal Patterns. Music Perception: An Interdisciplinary Journal, 2(4), 411-440. https: //doi.org/10.2307/40285311 google scholar
  • Pressing, J. (1999). Cognitive complexity and the structure of musical patterns. http://dub.ucsd.edu/Mu206/CogComplex-music.pdf google scholar
  • Shmulevich, I., & Povel, D. J. (2000). Measures of Temporal Pattern Complexity. Journal of New Music Research, 29(1), 61-69. https: //doi.org/10.1076/0929-8215(200003)29:01;1-P;FT061 google scholar
  • Smith, M. L., & Honing, H. (2006). Evaluating and Extending Computational Models of Rhythmic Syncopation in Music. International Computer Music Conference Proceedings, 2006. http://hdl.handle.net/2027/spo.bbp2372.2006.139 google scholar
  • Sternberg, S., Knoll, R., & Zukojsky, P. (1982). The Psychology of Music (pp. 181-239). Academic Press. http://www.musicalobservations.com/ publications/timing.pdf google scholar
  • Tanguiane, A. (1993). Artificial Perception and Music Recognition. In Springer eBooks. Springer Berlin, Heidelberg. https://doi.org/10.1007/ bfb0019384 google scholar
  • Tanguiane, A. (1994). A Principle of Correlativity of Perception and Its Application to Music Recognition. Music Perception, 11(4), 465-502. https://doi.org/10.2307/40285634 google scholar
  • Thomas, E. C., & Brown, I. (1974). Time perception and the filled-duration illusion. Perception & Psychophysics, 16(3), 449-458. https: //doi.org/10.3758/bf03198571 google scholar
  • Thul, E. (2008). Measuring the complexity of musical rhythm. Escholarship.mcgill.ca. C3S2E ’08: Proceedings of the 2008 C3S2E Conference. https://escholarship.mcgill.ca/concern/theses/r494vp484 google scholar
  • Toussaint, G. (2002). Mathematical Connections in Art, Music, and Science A Mathematical Analysis of African, Brazilian and Cuban Clave Rhythms. https://archive.bridgesmathart.org/2002/bridges2002-157.pdf google scholar
  • Toussaint, G. (2004). A Comparison Of Rhythmic Similarity Measures. International Society for Music Information Retrieval Conference. https://www.ee.columbia.edu/~dpwe/ismir2004/CRFILES/paper134.pdf google scholar
  • Toussaint, G. (2005a). Classification and Phylogenetic Analysis of African Ternary Rhythm Timelines. https://cgm.cs.mcgill.ca/~godfried/ teaching/mir-reading-assignments/Classification-and-Phylogenetic-Analysis-of-African-Ternary-Rhythm-Timelines.pdf google scholar
  • Toussaint, G. (2005b). The Euclidean Algorithm Generates Traditional Musical Rhythms. https://cgm.cs.mcgill.ca/~godfried/publications/ banff-extended.pdf google scholar

Müzik Performansında Ritmik Karmaşıklık Ölçümleri Üzerine Karşılaştırmalı Bir Çalışma

Yıl 2024, Cilt: 11 Sayı: 2, 478 - 487, 25.12.2024
https://doi.org/10.26650/CONS2024-1562373

Öz

Ritmik karmaşıklık çalışmaları, ritimlerin algısal karmaşıklığını, ne kadar kolay hatırlanıp icra edilebileceğini belirlemeyi amaçlayan bir araştırma alanıdır. Bu makalede, ritmik karmaşıklığa iki tamamlayıcı perspektiften yaklaşan (kavramsal algı ve ritmik kalıpların icrası.) iki ön çalışmanın sonuçlarını raporlanmıştır. Çalışmada beş ölçeğe odaklanılmıştır: Lempel-Ziv, Keith, Tanguiane, Weight Note-to-Beat Distance (WNBD) ve Pressing. Çalışmalarda kullanılan ritimler, Konservatuvar giriş sınavı soruları temel alınarak tasarlanan algoritmik yazılım tarafından oluşturulmuştur. İlk çalışmada, üç uzman değerlendirici, algoritmik olarak oluşturulan 80 ritim kalıbının uygunluğunu ve zorluğunu değerlendirmiştir. Verdikleri puanlar, karmaşıklık ölçeklerinden elde edilen değerlerle karşılaştırılmıştır. İkinci çalışmada 11 konservatuar öğrencisi (5 kadın, 6 erkek) ilk havuzdan seçilen 16 ritmi icra etmiştir.
Sonuçlar, farklı koşullar altında farklı ölçekler ve uzman tahminleri arasında değişen derecelerde uyum olduğunu göstermiştir. İlk çalışmada, Pressing, WNBD, Keith ve Tanguiane karmaşıklık ölçeklerinin uzman puanlayıcılarla tutarlı olduğu bulunmuştur. İkinci çalışmada, ritim tekrarı zorluğu için en doğru tahminleri uzman puanlayıcılar yapmış, bunu WNBD ölçeği ve Tanguiane ölçeği izlemiştir. Ayrıca, her bir soru için harcanan ortalama süre ile performans puanları arasında anlamlı bir negatif korelasyon bulunmuştur.

Proje Numarası

121E198

Kaynakça

  • Arom, S., & Ligeti, G. (1991). African Polyphony and Polyrhythm. (No Title). https://doi.org/10.1017/cbo9780511518317 google scholar
  • Baysal, O., & Bozkurt, B. (2022). MAST rhythm dataset [Data set]. Zenodo. https://doi.org/10.5281/zenodo.7243752 google scholar
  • Bolton, T. L. (1894). Rhythm. The American Journal of Psychology, 6(2), 145. https://doi.org/10.2307/1410948 google scholar
  • Buffardi, L. (1971). Factors affecting the filled-duration illusion in the auditory, tactual, and visual modalities. Perception & Psychophysics, 10(4), 292-294. https://doi.org/10.3758/bf03212828 google scholar
  • Clarke, E. F. (1987). Levels of structure in the organization of musical time. Contemporary Music Review, 2(1), 211-238. https://doi.org/10. 1080/07494468708567059 google scholar
  • de Fleurian, R., Blackwell, T., Ben-Tal, O., & Müllensiefen, D. (2016). Information-Theoretic Measures Predict the Human Judgment of Rhythm Complexity. Cognitive Science, 41(3), 800-813. https://doi.org/10.1111/cogs.12347 google scholar
  • Essens, P. (1995). Structuring temporal sequences: Comparison of models and factors of complexity. Perception & Psychophysics, 57(4), 519-532. https://doi.org/10.3758/bf03213077 google scholar
  • Fraisse, P. (1956). Fraisse (Paul). — Les Structures Rythmiques. Etude psychologique, Erasme, 1956, Bruxelles-Paris. Bulletin de Psychologie, 13(177), 655-657. https://www.persee.fr/doc/bupsy_0007-4403_1960_num_13_177_8359_t1_0655_0000_1 google scholar
  • Fraisse, P. (1982). Rhythm and Tempo. Psychology of Music, 1(1), 149-180. https://doi.org/10.1016/b978-0-12-213562-0.50010-3 google scholar
  • Gomez, F., Melvin, A., Rappaport, D., & Toussaint, G. (n.d.). Mathematical Measures of Syncopation. Retrieved January 31, 2024, from https://research.cs.queensu.ca/home/daver/Pubs/MyPDF/MeasureSycopa.pdf google scholar
  • Keith, M. (1991). From Polychords to Polya: Adventures in Musical Combinatorics. Vinculum Press. google scholar
  • Lempel, A., & Ziv, J. (1976). On the Complexity of Finite Sequences. IEEE Transactions on Information Theory, 22(1), 75-81. https: //doi.org/10.1109/tit.1976.1055501 google scholar
  • Lerdahl, F., & Jackendoff, R. S. (1996). A Generative Theory of Tonal Music, reissue, with a new preface. MIT Press. google scholar
  • Longuet-Higgins, H. C., & Lee, C. S. (1984). The Rhythmic Interpretation of Monophonic Music. Music Perception: An Interdisciplinary Journal, 1(4), 424-441. https://doi.org/10.2307/40285271 google scholar
  • Povel, D.-J. (1981). Internal representation of simple temporal patterns. Journal of Experimental Psychology: Human Perception and Perfor-mance, 7(1), 3-18. https://doi.org/10.1037/0096-1523.7.1.3 google scholar
  • Povel, D.-J. (1984). A theoretical framework for rhythm perception. Psychological Research, 45(4), 315-337. https://doi.org/10.1007/bf00309709 google scholar
  • Povel, D.-J., & Essens, P. (1985). Perception of Temporal Patterns. Music Perception: An Interdisciplinary Journal, 2(4), 411-440. https: //doi.org/10.2307/40285311 google scholar
  • Pressing, J. (1999). Cognitive complexity and the structure of musical patterns. http://dub.ucsd.edu/Mu206/CogComplex-music.pdf google scholar
  • Shmulevich, I., & Povel, D. J. (2000). Measures of Temporal Pattern Complexity. Journal of New Music Research, 29(1), 61-69. https: //doi.org/10.1076/0929-8215(200003)29:01;1-P;FT061 google scholar
  • Smith, M. L., & Honing, H. (2006). Evaluating and Extending Computational Models of Rhythmic Syncopation in Music. International Computer Music Conference Proceedings, 2006. http://hdl.handle.net/2027/spo.bbp2372.2006.139 google scholar
  • Sternberg, S., Knoll, R., & Zukojsky, P. (1982). The Psychology of Music (pp. 181-239). Academic Press. http://www.musicalobservations.com/ publications/timing.pdf google scholar
  • Tanguiane, A. (1993). Artificial Perception and Music Recognition. In Springer eBooks. Springer Berlin, Heidelberg. https://doi.org/10.1007/ bfb0019384 google scholar
  • Tanguiane, A. (1994). A Principle of Correlativity of Perception and Its Application to Music Recognition. Music Perception, 11(4), 465-502. https://doi.org/10.2307/40285634 google scholar
  • Thomas, E. C., & Brown, I. (1974). Time perception and the filled-duration illusion. Perception & Psychophysics, 16(3), 449-458. https: //doi.org/10.3758/bf03198571 google scholar
  • Thul, E. (2008). Measuring the complexity of musical rhythm. Escholarship.mcgill.ca. C3S2E ’08: Proceedings of the 2008 C3S2E Conference. https://escholarship.mcgill.ca/concern/theses/r494vp484 google scholar
  • Toussaint, G. (2002). Mathematical Connections in Art, Music, and Science A Mathematical Analysis of African, Brazilian and Cuban Clave Rhythms. https://archive.bridgesmathart.org/2002/bridges2002-157.pdf google scholar
  • Toussaint, G. (2004). A Comparison Of Rhythmic Similarity Measures. International Society for Music Information Retrieval Conference. https://www.ee.columbia.edu/~dpwe/ismir2004/CRFILES/paper134.pdf google scholar
  • Toussaint, G. (2005a). Classification and Phylogenetic Analysis of African Ternary Rhythm Timelines. https://cgm.cs.mcgill.ca/~godfried/ teaching/mir-reading-assignments/Classification-and-Phylogenetic-Analysis-of-African-Ternary-Rhythm-Timelines.pdf google scholar
  • Toussaint, G. (2005b). The Euclidean Algorithm Generates Traditional Musical Rhythms. https://cgm.cs.mcgill.ca/~godfried/publications/ banff-extended.pdf google scholar
Toplam 29 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Müzik (Diğer)
Bölüm Araştırma Makalesi
Yazarlar

Cihan Yaygın 0000-0002-3329-3650

Ozan Baysal 0000-0002-7271-9095

Yavuz Buruk 0009-0001-2223-6087

Barış Bozkurt 0000-0002-0177-0758

Proje Numarası 121E198
Yayımlanma Tarihi 25 Aralık 2024
Gönderilme Tarihi 6 Ekim 2024
Kabul Tarihi 29 Kasım 2024
Yayımlandığı Sayı Yıl 2024 Cilt: 11 Sayı: 2

Kaynak Göster

APA Yaygın, C., Baysal, O., Buruk, Y., Bozkurt, B. (2024). A Comparative Study of Rhythmic Complexity Measures in Music Performance. Konservatoryum, 11(2), 478-487. https://doi.org/10.26650/CONS2024-1562373