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Analyzing the perception of Chinese melodic imagery and its application to automated composition

机译:分析中国旋律意象及其在自动构图中的应用

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This study investigated the influence of two music elements, mode and rhythm, on melodic imagery. By modulating different parameters of mode and rhythm, this study produced various melody samples. Kansei engineering was adopted as a research method for designing the experimental process. A set of music assessment rules was established by regularizing the existing modes and rhythms and analyzing and comparing their differences. The results were applied to automated composition in order to develop a comprehensive automated composition system. Before the hearing experiment, 39 adjective pairs were selected for the survey of melodic imagery by reviewing literature and engaging in discussions with experts. A Markov chain was adopted for analyzing the current modal music to establish a Markov switching table for the Chinese pentatonic scale, and metrical complexity was used for generating rhythms. Finally, 30 music samples were produced using the automated composition system by applying the various combinations of modes and rhythms. The hearing experiment was conducted on 35 participants for examining their perception of melodic imagery. Item analysis and a reliability test were performed on the experimental data for eliminating invalid samples and items. Thus, 14 adjective pairs with a Cronbach's alpha of 0.887 were obtained, indicating favorable reliability. In addition, this study involved conducting factor analysis and extracting three imagery factors, namely passionate-apathetic, beautiful-ugly, and romantic-rigid. Subsequently, multivariate analysis of variance was conducted in this study for determining the relationship between modes and metrical complexity and the 14 adjective pairs, and the estimated means were calculated. Multidimensional scaling was adopted for producing a two-dimensional perceptual map for the construction of a database. The experimental results of this study showed that modes and rhythms in music can effectively help musicians or computer composition systems compose melodies that create various perceptual imageries.
机译:这项研究调查了两种音乐元素(模式和节奏)对旋律图像的影响。通过调节模式和节奏的不同参数,本研究产生了各种旋律样本。采用Kansei工程作为设计实验过程的研究方法。通过规范现有的模式和节奏并分析和比较它们之间的差异,建立了一套音乐评估规则。将结果应用于自动合成,以开发一个全面的自动化合成系统。在听力实验之前,通过回顾文献并与专家进行讨论,选择了39个形容词对进行旋律图像的调查。采用马尔可夫链分析当前的模态音乐,以建立中国五音阶的马尔可夫切换表,并用音调复杂度产生节奏。最终,使用自动组合系统通过应用模式和节奏的各种组合制作了30个音乐样本。对35名参与者进行了听力实验,以检查他们对旋律图像的感知。对实验数据进行了项目分析和可靠性测试,以消除无效的样本和项目。因此,获得14对形容词对,其克伦巴赫α值为0.887,表明其具有良好的可靠性。此外,这项研究涉及进行因素分析并提取三个图像因素,即热情冷漠,美丽丑陋和浪漫僵硬。随后,在这项研究中进行了方差的多元分析,以确定模式和度量复杂性之间的关系以及14个形容词对,并计算了估计均值。采用多维缩放来生成二维感知图,以用于数据库的构建。这项研究的实验结果表明,音乐中的模式和节奏可以有效地帮助音乐家或计算机组成系统组成旋律,从而创造出各种感知图像。

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