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

机译:对音乐分数自动转录过程中应用不同进化方法的评价

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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:将音乐在标准音乐符号(音乐表)中转换为吉他平台的替代符号的问题称为转录。转录过程包括指示原始音乐表所需的每个笔记需要在吉他中播放,即需要播放的吉他的绳子和褶皱以产生特定的音符。然而,考虑到每个音符可以在吉他脚板的不同位置播放,这不是一个直接的过程,并且可以被归类为组合优化问题。因此,我们使用了不同算法的比较研究:A-STAR,遗传算法(GA),基于亚步骤(GA-SP),蚁群优化(ACO)和差分进化(DE)的遗传算法。它还包括基于本地搜索2-opt和3-opt的启发式方法,并在接近的方法,GA-SP和DE。具有87个音乐数据集的实验结果表明,ACO,GA-SP与2-OPT和GA,GA-SOPY达到了最佳性能。此外,使用与后HOC Tukey的ANOVA测试进行统计比较,通过每种方法获得的结果。

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