The potential of artificial intelligence in musical analysis: A comparative study of a Baroque period piano piece analyzed by human and artificial intelligence
Abstract
The purpose of this study is to compare the form and harmonic analyses of the piano piece Der
Erste Bach-Menuet I by the Baroque composer Johann Sebastian Bach, conducted by both human
and artificial intelligence. The study employed the document analysis method, one of the
qualitative research designs. The form and harmonic structures were examined both by an AIbased analytical tool and by an academician specializing in music, and these analyses were
comparatively evaluated. In the AI-based analysis process, the GPT-4-based ChatGPT model was
used. The musical data were uploaded to the model in MIDI format, and the formal and harmonic
structures were interpreted through a natural language processing infrastructure. The findings
revealed that while human analysis was superior in interpretive power, pedagogical value, and
contextual depth, the technical accuracy and speed of AI make it a valuable complementary
resource, particularly in rule-based areas such as harmonic analysis
References
- Aksu, H. (2018). Dijitopya dijital dönüşüm yolculuk rehberi (1. baskı). Pusula.
- Boden, M. A. (2010). Creativity and art: Three roads to surprise (1. baskı). Oxford University.
- Buttol, V. (2023). Ethical implications of artificial intelligence: The relationship between algorithms and kindness (Yüksek lisans tezi). Ca’ Foscari Üniversitesi, Venedik.
- Canan, S. ve Acungil, M. (2018). Dijital gelecekte insan kalmak (1. baskı). Nefes.
- Cope, D. (1992). Computer modeling of musical intelligence in EMI. Computer music journal, 16(2), 69-83. https://doi.org/10.2307/3680717
- Creswell, J. W. (2007). Qualitative inquiry and research design (2. baskı). Sage.
- Dutton, D. (2009). The art instinct: Beauty, pleasure, & human evolution (1. baskı). Oxford University.
- Eberl, U. (2019). Akıllı makineler yapay zekâ hayatımızı nasıl değiştiriyor (1. baskı) (Çev. L. Tayla). Paloma.
- Fernández, J. ve Vico, F. (2013). AI methods in algorithmic composition: A comprehensive survey. Journal of artificial intelligence research, 48, 513-582.https://doi.org/10.1613/jair.3908
- Guba, E. G. ve Lincoln, Y. S. (1994). Competing paradigms in qualitative research. Handbook of qualitative research, 2(105), 163-194.
- Gürel, M. (2017). Dijital Kehanet (1. baskı). Destek.
- Jenkins, O. C., Lopresti, D. ve Mitchell, M. (2020). Next wave artificial intelligence: Robust, explainable, adaptable, ethical, and accountable. https://arxiv.org/abs/2012.06058
- Kaplan, A. ve Haenlein, M. (2019). Siri, Siri, in my hand: Who’s the fairest in the land? On the interpretations, illustrations, and implications of artificial intelligence. Business horizons, 62(1), 15-25. https://doi.org/10.1016/j.bushor.2018.08.004
- Klenke, K. (2016). Qualitative research in the study of leadership (1. baskı). Emerald Group.
- Koç, O. (2018). Daha iyi bir dünya için yapay zekâ (1. baskı). Doğan Egmont.
- Korteling, J. E., Van de Boer-Visschedijk, G. C., Blankendaal, R. A., Boonekamp, R. C. ve Eikelboom, A. R. (2021). Human-versus artificial intelligence. Frontiers in artificial intelligence, 4, 622364. https://doi.org/10.3389/frai.2021.622364
- Lu, J., Gong, P., Ye, J., Zhang, J. ve Zhang, C. (2023). A survey on machine learning from few samples. Pattern recognition, 139, 109480. https://doi.org/10.1016/j.patcog.2023.109480
- OpenAI (2019, Nisan). MuseNet. https://openai.com/research/musenet/
- Singil, N. (2022). Yapay zekâ ve insan hakları. Public and private international law bulletin, 42(1), 121-158. https://doi.org/10.26650/ppil.2022.42.1.970856
- Sturm, B., Ben-Tal, O., Monaghan, Ú., Collins, N., Herremans, D., Chew, E. ve Pachet, F. (2018). Machine learning research that matters for music creation: A case study. Journal of new music research, 48(1), 36-55. https://doi.org/10.1080/09298215.2018.1515233
- Tegmark, M. (2019). Yaşam 3.0: Yapay zekâ çağında insan olmak (1. baskı) (Çev. E. C. Göksoy). Pegasus.
- Tymoczko, D. ve Newman, M. (2024). Computational music analysis from first principles. https://doi.org/10.48550/arXiv.2407.21130
- Wang, Z., Min, L. ve Xia, G. (2024). Whole-song hierarchical generation of symbolic music using cascaded diffusion models. In proceedings of the international conference on learning representations. https://doi.org/10.48550/arXiv.2405.09901
- Wenhui, J. (2021). Thoughts on the interaction between AI technology and music education. Sichuan drama, 9, 170-172.
- Yıldırım, A. ve Şimşek, H. (2021). Sosyal bilimlerde nitel araştırma yöntemleri. (12. baskı). Seçkin.
- Zhang, Y., Fen, B. W., Zhang, C. ve Pi, S. (2024). Transforming music education through artificial intelligence: A systematic literature review on enhancing music teaching and learning. International Journal of interactive mobile technologies, 18(18) 76-93. https://doi.org/10.3991/ijim.v18i18.50545
- Zhu, Y., Baca, J., Rekabdar, B. ve Rawassizadeh, R. (2023). A survey of AI music generation tools and models. https://arxiv.org/abs/2308.12982
Müziksel analizde yapay zekânın potansiyeli: Bir Barok dönem piyano eserinin insan ve yapay zekâ tarafından karşılaştırmalı analizi
Abstract
Bu araştırmanın amacı, Barok dönem bestecilerinden Johann Sebastian Bach’a ait Der Erste BachMenuet I adlı piyano eserinin insan ve yapay zekâ tarafından yapılan form ve armonik analizinin
karşılaştırılmasıdır. Araştırmada, nitel araştırma desenlerinden doküman incelemesi yöntemi
kullanılmıştır. Araştırmada, eserin form ve armonik yapısı hem yapay zekâ tabanlı bir analiz aracı
hem de müzik alanında bir akademisyen tarafından incelenmiş, bu analizler karşılaştırmalı olarak
değerlendirilmiştir. Araştırmanın yapay zekâ temelli analiz sürecinde, GPT-4 tabanlı ChatGPT
modeli kullanılmıştır. Yapay zekâ analiz sürecinde, müzikal veri MIDI formatında modele
yüklenmiş; form ve armonik yapılar, doğal dil işleme altyapısıyla yorumlanmıştır. Araştırma
sonucunda, insan tarafından yapılan analizlerin, yapay zekâya kıyasla yorum gücü, pedagojik
değeri ve bağlamsal derinlik açısından daha üstün olduğu, ancak yapay zekânın sunduğu teknik
doğruluk ve hız, özellikle armonik analiz gibi kurallara dayalı alanlarda tamamlayıcı bir kaynak
olarak değerlendirilebileceği ortaya konmuştur
Keywords
References
- Aksu, H. (2018). Dijitopya dijital dönüşüm yolculuk rehberi (1. baskı). Pusula.
- Boden, M. A. (2010). Creativity and art: Three roads to surprise (1. baskı). Oxford University.
- Buttol, V. (2023). Ethical implications of artificial intelligence: The relationship between algorithms and kindness (Yüksek lisans tezi). Ca’ Foscari Üniversitesi, Venedik.
- Canan, S. ve Acungil, M. (2018). Dijital gelecekte insan kalmak (1. baskı). Nefes.
- Cope, D. (1992). Computer modeling of musical intelligence in EMI. Computer music journal, 16(2), 69-83. https://doi.org/10.2307/3680717
- Creswell, J. W. (2007). Qualitative inquiry and research design (2. baskı). Sage.
- Dutton, D. (2009). The art instinct: Beauty, pleasure, & human evolution (1. baskı). Oxford University.
- Eberl, U. (2019). Akıllı makineler yapay zekâ hayatımızı nasıl değiştiriyor (1. baskı) (Çev. L. Tayla). Paloma.
- Fernández, J. ve Vico, F. (2013). AI methods in algorithmic composition: A comprehensive survey. Journal of artificial intelligence research, 48, 513-582.https://doi.org/10.1613/jair.3908
- Guba, E. G. ve Lincoln, Y. S. (1994). Competing paradigms in qualitative research. Handbook of qualitative research, 2(105), 163-194.
- Gürel, M. (2017). Dijital Kehanet (1. baskı). Destek.
- Jenkins, O. C., Lopresti, D. ve Mitchell, M. (2020). Next wave artificial intelligence: Robust, explainable, adaptable, ethical, and accountable. https://arxiv.org/abs/2012.06058
- Kaplan, A. ve Haenlein, M. (2019). Siri, Siri, in my hand: Who’s the fairest in the land? On the interpretations, illustrations, and implications of artificial intelligence. Business horizons, 62(1), 15-25. https://doi.org/10.1016/j.bushor.2018.08.004
- Klenke, K. (2016). Qualitative research in the study of leadership (1. baskı). Emerald Group.
- Koç, O. (2018). Daha iyi bir dünya için yapay zekâ (1. baskı). Doğan Egmont.
- Korteling, J. E., Van de Boer-Visschedijk, G. C., Blankendaal, R. A., Boonekamp, R. C. ve Eikelboom, A. R. (2021). Human-versus artificial intelligence. Frontiers in artificial intelligence, 4, 622364. https://doi.org/10.3389/frai.2021.622364
- Lu, J., Gong, P., Ye, J., Zhang, J. ve Zhang, C. (2023). A survey on machine learning from few samples. Pattern recognition, 139, 109480. https://doi.org/10.1016/j.patcog.2023.109480
- OpenAI (2019, Nisan). MuseNet. https://openai.com/research/musenet/
- Singil, N. (2022). Yapay zekâ ve insan hakları. Public and private international law bulletin, 42(1), 121-158. https://doi.org/10.26650/ppil.2022.42.1.970856
- Sturm, B., Ben-Tal, O., Monaghan, Ú., Collins, N., Herremans, D., Chew, E. ve Pachet, F. (2018). Machine learning research that matters for music creation: A case study. Journal of new music research, 48(1), 36-55. https://doi.org/10.1080/09298215.2018.1515233
- Tegmark, M. (2019). Yaşam 3.0: Yapay zekâ çağında insan olmak (1. baskı) (Çev. E. C. Göksoy). Pegasus.
- Tymoczko, D. ve Newman, M. (2024). Computational music analysis from first principles. https://doi.org/10.48550/arXiv.2407.21130
- Wang, Z., Min, L. ve Xia, G. (2024). Whole-song hierarchical generation of symbolic music using cascaded diffusion models. In proceedings of the international conference on learning representations. https://doi.org/10.48550/arXiv.2405.09901
- Wenhui, J. (2021). Thoughts on the interaction between AI technology and music education. Sichuan drama, 9, 170-172.
- Yıldırım, A. ve Şimşek, H. (2021). Sosyal bilimlerde nitel araştırma yöntemleri. (12. baskı). Seçkin.
- Zhang, Y., Fen, B. W., Zhang, C. ve Pi, S. (2024). Transforming music education through artificial intelligence: A systematic literature review on enhancing music teaching and learning. International Journal of interactive mobile technologies, 18(18) 76-93. https://doi.org/10.3991/ijim.v18i18.50545
- Zhu, Y., Baca, J., Rekabdar, B. ve Rawassizadeh, R. (2023). A survey of AI music generation tools and models. https://arxiv.org/abs/2308.12982
Details
| Primary Language | Turkish |
|---|---|
| Subjects | Arts and Cultural Policy |
| Journal Section | Research Articles |
| Authors | |
| Publication Date | October 22, 2025 |
| Submission Date | July 15, 2025 |
| Acceptance Date | October 8, 2025 |
| Published in Issue | Year 2025 Issue: Yapay zekâ ve sanat özel sayısı |
ARTS is licensed under CC BY-NC 4.0 
PUBLISHER | JOURNAL BOARDS | INDEXES | PRICE POLICY | STATISTICS | MIAR | SHERPA ROMEO