TY  - JOUR
T1  - RESEARCH ON THE CONSTRUCTION OF AI COMPOSITION SYSTEM BASED ON HMM
TT  - HMMS TEMELLİ YAPAY ZEKA BESTECİLİĞİ SİSTEMİ İNŞASI ÜZERİNE BİR ARAŞTIRMA
AU  - Lee, Inho
AU  - Yang, Weijia
PY  - 2024
DA  - September
Y2  - 2024
DO  - 10.51576/ymd.1536267
JF  - Yegah Müzikoloji Dergisi
JO  - YMD
PB  - Tolga KARACA
WT  - DergiPark
SN  - 2792-0178
SP  - 216
EP  - 240
VL  - 7
IS  - 3
LA  - en
AB  - The Markov chain is an automatic accompaniment algorithm for intelligent computer systems, belonging to the interdisciplinary research field of musicology and computer science. Currently, there are many methods for AI music generation, but research on AI music generation based on the Hidden Markov Model (HMM) is relatively scarce. This paper proposes a method for constructing an AI composition system based on the HMM. This system achieves the goal of automatically generating accompaniment music from score data. The proposed system has achieved relatively stable results in the generation of musical elements such as form and harmony, accompaniment texture, and instrumentation, and has scored well in evaluation experiments.
KW  - Automatic accompaniment algorithm
KW  - Artificial Intelligence
KW  - Composition
KW  - Popular music
KW  - Hidden Markov Model.
N2  - Yapay Zeka (AI) çağı geldi ve önemli bir konu olan yapay zeka ile besteleme büyük ilgi görmektedir. Şu anda, müzikoloji ve bilgisayar bilimi disiplinler arası araştırma alanında birçok otomatik besteleme algoritması bulunmaktadır ve Markov zinciri, zeki bilgisayar sistemleri için temsil edici bir otomatik eşlik algoritmasıdır. Büyük veri çağının gelmesiyle birlikte, olasılık teorisine dayalı bir otomatik besteleme yöntemi olan Markov zinciri yavaş yavaş göz ardı edilmeye başlanmıştır. Ancak, Gizli Markov Modeli (HMM) temelli yapay zeka müzik üretimi üzerine yapılan araştırmalar hala çok değerlidir. Bu makale, popüler müzik tarzı için HMM'ye dayalı bir yapay zeka beste sistemi inşa etme yöntemini önermektedir. Bu sistem, nota verilerinden otomatik olarak eşlik müziği üretme hedefini gerçekleştirmektedir. Önerilen sistem, form ve uyum, eşlik dokusu ve enstrümantasyon gibi müzikal unsurların üretilmesinde görece istikrarlı sonuçlar elde etmiş ve değerlendirme deneylerinde iyi notlar almıştır. Bu çalışma, yapay zeka çağında algoritmik besteleme mühendisliği örneklerinin inşası yoluyla müzikoloji araştırmalarının teknik sınırlarını deneysel bir şekilde keşfetmeyi amaçlamaktadır.
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UR  - https://doi.org/10.51576/ymd.1536267
L1  - https://dergipark.org.tr/tr/download/article-file/4158232
ER  -