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An Evaluation of Different Evolutionary Approaches Applied in the Process of Automatic Transcription of Music Scores into Tablatures

机译:乐谱自动抄录到制谱过程中应用的不同进化方法的评估

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The problem of converting a music in standard music notation (music sheet) to the alternative notation of guitar tablature is known as transcription. The process of transcription consists of indicating where each note from the original music sheet needs to be played in the guitar, i.e. which string and fret of the guitar that needs to be played to produce a particular note. However, considering that each note can be played in different positions of the guitar fretboard, this is not a straightforward process, and can be classified as a combinatorial optimization problem. For this reason, we have employed a comparative study of different algorithms: A-star, genetic algorithms (GA), genetic algorithms based on subpopulations (GA-SP), ant colony optimization (ACO) and differential evolution (DE). It was also included heuristics based on local search 2-opt and 3-opt in the approaches GA, GA-SP and DE. The experimental results with a dataset of 87 musics indicated that the approaches ACO, GA-SP with 2-opt and GA with 2-opt reached the best performance. Also, the results obtained with each approach were statistically compared using ANOVA test with post hoc Tukey.
机译:将标准音乐符号(乐谱)中的音乐转换为吉他谱的替代符号的问题被称为转录。转录过程包括指示原始乐谱中的每个音符需要在吉他中弹奏的位置,即,需要演奏吉他的哪根弦和弦才能产生特定的音符。但是,考虑到每个音符可以在吉他指板的不同位置弹奏,这不是一个简单的过程,可以归类为组合优化问题。因此,我们对不同算法进行了比较研究:A-star,遗传算法(GA),基于亚种群的遗传算法(GA-SP),蚁群优化(ACO)和差异进化(DE)。在方法GA,GA-SP和DE中,还包括基于本地搜索2-opt和3-opt的启发式方法。包含87个音乐的数据集的实验结果表明,采用2 opt的ACO,GA-SP和采用2 opt的GA的方法达到了最佳性能。此外,使用ANOVA测试和事后Tukey对每种方法获得的结果进行统计比较。

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