RESEARCH ON THE CONSTRUCTION OF AI COMPOSITION SYSTEM BASED ON HMM

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.

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Publication Details

Journal
Yegah Müzikoloji Dergisi
Published
2024-09-09
DOI
https://doi.org/10.51576/ymd.1536267
Citations
1
Primary Topic
Music Technology and Sound Studies
Type
article
Field-Weighted Citation Impact
0.25

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article

RESEARCH ON THE CONSTRUCTION OF AI COMPOSITION SYSTEM BASED ON HMM

Weijia Yang, Inho Lee
1 citations
Yegah Müzikoloji Dergisi
Music Technology and Sound Studies
0.25
article

RESEARCH ON THE CONSTRUCTION OF AI COMPOSITION SYSTEM BASED ON HMM

Weijia Yang, Inho Lee
article en
1 citations

Abstract

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.

Yegah Müzikoloji DergisiVol. 7(3)
Kyonggi University (KR)
Kyonggi University
Quality Education
Openalex Percentile: Top 48%
Music Technology and Sound Studies
0.25
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