Research Information System
Thesis Type: Postgraduate
Institution Of The Thesis: Marmara University, Institute of Social Sciences, Department of Islamic History and Arts, Turkey
Approval Date: 2024
Thesis Language: Turkish
Student: HASAN KAMİL GENÇ
Supervisor: Mehmet Safa Yeprem
Abstract:
Artificial intelligence (AI) has undergone remarkable advancements since the 1940s, permeating various sectors and becoming an integral part of life. Music is one such domain where AI has made significant inroads. As a matter of fact, there are various AI-powered music composition tools today. However, studies on composing Turkish maqām music with AI are almost non-existent. This study investigates the ability of AI to generate a composition in rast maqām, rhythmic cycle of sofyān, and ilāhī form of Turkish music, using ChatGPT as an example. In the composition process, ChatGPT's knowledge of ilāhī form, rast maqām, and rhythmic cycle of sofyān was augmented through machine learning techniques. Three ilāhī samples were provided to the chatbot using a text-based notation system developed by the author. As a result of the process consisting of 69 prompts, the composition in rast maqām and rhythmic cycle of sofyān was analyzed comparatively. The analysis is based on the rules of rast maqām, the meter structure and the composition scheme of ilāhī form, and its similarity to the ilāhīs composed in the historical process. The rate of similarity was determined based on aspects such as the starting pitches, the highest and lowest pitches in the melodic progression, the flavors used in the progression, the use of the sansibl (yadan) before the finalis and the number of flavors. In conclusion, when compared with a sample from the Turkish religious music repertoire that can be considered to represent the ilāhīs in the rast maqām and the rhythmic cycle of sofyān, the composition created by ChatGPT was found to possess characteristics that align with the maqām, the meter structure and the composition scheme of the ilāhī form.