Markov-based genetic algorithm with ϵ-greedy exploration for Indian classical music composition. (January 2023)

• Record Type: Journal Article
• Authors: Shukla, Shipra; Banka, Haider
• Is Part Of: Expert systems with applications. Volume 211(2023)
• Publication Date: 2023-01
• Subjects: Music composition -- Genetic algorithm -- ε-greedy exploration -- Markov chain -- Indian classical music; Expert systems (Computer science) -- Periodicals; Systèmes experts (Informatique) -- Périodiques; Electronic journals; 006.33
• DOI: 10.1016/j.eswa.2022.118561
• Languages: English
• ISSNs: 0957-4174

Abstract

Abstract: Recent technological advancements have made it possible to automate some of the intricate activities involved in music production. In this paper, a heuristic method is proposed for automatic composition of Indian Classical Music (ICM). Composing ICM necessitates consideration of raga constraints which distinguishes it from other genres of music. The raga-based music cannot be generated through random exploration of search space. More specifically, certain disordering in note combinations can violate the raga constraints. To address the aforesaid issue, the paper proposes a novel method by combining genetic algorithm with Markov chain model attuned to ICM sequences. Moreover, the proposed method uses ϵ -greedy strategy to balance the exploration and exploitation of musical search space. In order to preserve the musical characteristics, domain-specific genetic operators (i.e., crossover and mutation) are defined. The evaluation function based on music theory is used to direct the search to favorable tracks. The Kullback Liebler (KL) divergence metric is used to analyze the probability distribution of output and sample data sequence. The results indicate that by regulating the exploration rate, the method is capable of generating melodic sequences while maintaining the desired musical note distribution. Moreover, the method converges faster than the conventional genetic algorithm. Highlights: A new heuristic method for Indian Classical Music composition is proposed. Genetic algorithm and Markov chain are combined to produce musical sequences. The ϵ -greedy strategy balances exploration and exploitation of search space. Result analysis and comparisons verify the effectiveness of the proposed method.