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An evaluation of linear and non-linear models of expressive dynamics in classical piano and symphonic music

机译:古典钢琴和交响音乐中表现动力学的线性和非线性模型的评估

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Expressive interpretation forms an important but complex aspect of music, particularly in Western classical music. Modeling the relation between musical expression and structural aspects of the score being performed is an ongoing line of research. Prior work has shown that some simple numerical descriptors of the score (capturing dynamics annotations and pitch) are effective for predicting expressive dynamics in classical piano performances. Nevertheless, the features have only been tested in a very simple linear regression model. In this work, we explore the potential of non-linear and temporal modeling of expressive dynamics. Using a set of descriptors that capture different types of structure in the musical score, we compare linear and different non-linear models in a large-scale evaluation on three different corpora, involving both piano and orchestral music. To the best of our knowledge, this is the first study where models of musical expression are evaluated on both types of music. We show that, in addition to being more accurate, non-linear models describe interactions between numerical descriptors that linear models do not.
机译:富有表现力的诠释构成音乐的一个重要但复杂的方面,尤其是在西方古典音乐中。对音乐表达和所执行乐谱的结构方面之间的关系进行建模是一项正在进行的研究。先前的工作表明,一些简单的乐谱数字描述符(捕捉动态注释和音高)可有效预测古典钢琴演奏中的表现动态。但是,这些功能仅在非常简单的线性回归模型中进行过测试。在这项工作中,我们探索了表现动力学的非线性和时间建模的潜力。通过使用一组描述符来捕获乐谱中不同类型的结构,我们在涉及钢琴和管弦乐的三种不同语料库的大规模评估中,比较了线性模型和不同非线性模型。据我们所知,这是首次对两种音乐类型的音乐表现模型进行评估的研究。我们表明,除了更精确之外,非线性模型还描述了线性模型所不能描述的数字描述符之间的相互作用。

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