A Critical Review: The Implementation of Spectrogram and Sonic Visualizer on The Performance Review of Classical Music

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Herry Rizal Djahwasi
Abdul Rahman bin Safian
Muchammad Bayu Tejo Sampurno
Zaharul Lailiddin bin Saidon
Apichai Chantanakajornfun

Abstract

This Study examines the implementation of spectrogram and Sonic Visualizer tools in the performance analysis of classical music. Traditional methods of performance feedback often rely on subjective verbal criticism, which can be inconsistent and influenced by personal biases. This study highlights the limitations of these traditional approaches and the challenges posed by reliance on memory. Spectrograms and Sonic Visualizer provide objective, visual feedback that can reveal intricate patterns and details in musical performances not easily discernible through auditory perception alone. These tools offer precise feedback on pitch and timing, which is especially beneficial in educational settings. The study analyzes four key articles: Yasushi Ueda's investigation of tempo rubato in Chopin’s Nocturne Op.15-2, Cook & Leech-Wilkinson's guide to Sonic Visualizer, Garner's thesis on Schubert's Winterreise, and Gardiner and Latartara’s examination of Beethoven's "Hammerklavier" sonata. These studies demonstrate how features such as tempo and dynamic visualization, harmonic analysis, and beat detection aid performers in evaluating rhythmic accuracy, consistency, and interpretative choices. Moreover, the review identifies gaps in existing research, particularly the need for more comprehensive studies on the effectiveness of Sonic Visualizer across different classical instruments and its impact on performers' interpretative skills. The findings suggest that regular use of these tools can enhance performers' decision-making processes, creativity, and overall artistic growth. This study underscores the significant benefits of integrating advanced audio-visual tools into classical music performance analysis, providing a deeper understanding and more accurate assessment of musical interpretations.

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How to Cite
Djahwasi, H. R., bin Safian, A. R. ., Sampurno, M. B. T., bin Saidon, Z. L. ., & Chantanakajornfun, A. (2024). A Critical Review: The Implementation of Spectrogram and Sonic Visualizer on The Performance Review of Classical Music. Virtuoso: Jurnal Pengkajian Dan Penciptaan Musik, 7(1), 31–46. https://doi.org/10.26740/vt.v7n1.p31-46
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References

Barthet, M., & Dixon, S. (2011). Ethnographic observations of musicologists at the british library: Implications for music information retrieval. Proceedings of the 12th International Society for Music Information Retrieval Conference, ISMIR 2011, Ismir, 353–358.

Bowen, J. A. (1996). Tempo, duration, and flexibility: Techniques in the analysis of performance. Journal of Musicological Research, 16(2), 111–156.

Brown, J. C., & Puckette, M. S. (1992). An efficient algorithm for the calculation of a constant Q transform . The Journal of the Acoustical Society of America, 92(5), 2698–2701. https://doi.org/10.1121/1.404385

Clayton, M. (2020). Empirical methods in the study of music performance: An interdisciplinary history. In Investigating Musical Performance (pp. 9–24). Routledge.

Cogan, R. (1984). New images of musical sound. (No Title).

Cook, N., & Leech-Wilkinson, D. (2009a). A musicologist’s guide to Sonic Visualiser. London: Centre for the History and Analysis of Recorded Music. Http://Www. Charm. Rhul. Ac. Uk/Analysing/P9_1. Html (Accessed August 11, 2011).

Cook, N., & Leech-Wilkinson, D. (2009b). Techniques for analysing recordings: an introduction.

Ericsson, K. A. (2006). The influence of experience and deliberate practice on the development of superior expert performance. The Cambridge Handbook of Expertise and Expert Performance, 38(685–705), 2.

Ericsson, K. A., Krampe, R. T., & Tesch-Römer, C. (1993). The role of deliberate practice in the acquisition of expert performance. Psychological Review, 100(3), 363.

Gardiner, M., & Latartara, J. (2007). Analysis, Performance, and Images of Musical Sound: Surfaces, Cyclical Relationships and the Musical Work. Current Musicology, 84.

Gardiner, M., & Lim, J. S. (2014). Chromatopes of Noh: An Analysis of Timbral Progressions in the Introductions to Three Plays. Asian Music, 84–128.

Garner, S. C. (2021). Explorations of Timbre in Selected Songs from Schubert’s Winterreise. The University of Mississippi.

Hallam, S. (1997). What do we know about practicing? Towards a model synthesising the research literature. Does Practice Make Perfect? Current Theory and Research on Instrumental Music Practice, 1, 179–231.

Hattie, J., & Timperley, H. (2007). The Power of Feedback. Review of Educational Research, 77(1), 81–112. https://doi.org/10.3102/003465430298487

Hattie, T. (2007). Hattie, J., Timperley H. The Power of Feedback. Review of Educational Research, 77(1), 81–112.

Lavengood, M. L. (2020). The cultural significance of timbre analysis: A case study in 1980s pop music, texture, and narrative. Music Theory Online, 26(3).

McAdams, S. E., & Bigand, E. E. (1993). Thinking in sound: The cognitive psychology of human audition. Based on the Fourth Workshop in the Tutorial Workshop Series Organized by the Hearing Group of the French Acoustical Society.

Pons, J., Slizovskaia, O., Gong, R., Gómez, E., & Serra, X. (2017). Timbre analysis of music audio signals with convolutional neural networks. 2017 25th European Signal Processing Conference (EUSIPCO), 2744–2748.

Repp, B. H. (1992). A constraint on the expressive timing of a melodic gesture: Evidence from performance and aesthetic judgment. Music Perception, 10(2), 221–241.

Segnini, R., & Sapp, C. (2005). Scoregram: Displaying gross timbre information from a score. International Symposium on Computer Music Modeling and Retrieval, 54–59.

Ueda, Y. (2021). Tempo Rubato as Rhetorical Means: An Analysis of the Performance of Chopin’s Nocturne Op. 15-2 by Camille Saint-Saëns (1905). Časopis Srpskog Društva Za Muzičku Teoriju (Journal of the Serbian Society for Music Theory), 1(1), 34–54.