A music search system for expressive music performance learning

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Abstract

In this paper, we present a music search system that focuses on performance style to cultivate a pupil's expressive performance of music. The system allows pupils to learn the performance style to be mastered by obtaining both model and non-model content. By browsing non-model content that is similar to the quality of a pupil's performance, the pupil can quickly identify his/her areas that require improvement. In addition, the pupil can improve his/her performance skill by repeatedly imitating the models. We evaluate the capabilities of our music search system regarding the extraction of performance style from a classical music source and the precision of the music search results for performance style. © 2014 Springer International Publishing.

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APA

Mikami, T., & Takano, K. (2014). A music search system for expressive music performance learning. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8522 LNCS, pp. 80–89). Springer Verlag. https://doi.org/10.1007/978-3-319-07863-2_9

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