Research on character tone trend clustering of Kunqu Opera based on quantum adaptive genetic algorithm.

Kunqu, one of the oldest forms of Chinese opera, features a unique artistic expression arising from the interplay between vocal melody and the tonal quality of its lyrics. Identifying Kunqu's character tone trend (vocal melodies derived from tonal quality of the lyrics) is critical to understanding...

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Publicado en:Digital Scholarship in the Humanities Vol. 39; no. 1; pp. 393 - 409
Autores principales: Tian, Rui, Yin, Ruheng, Ban, Junrong
Formato: Artículo
Publicado: Oxford University Press / USA Apr2024
Materias:
Acceso en línea:Ver este registro en EBSCOhost
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        atl: Research on character tone trend clustering of Kunqu Opera based on quantum adaptive genetic algorithm.
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          Tian, Rui
          Yin, Ruheng
          Ban, Junrong
        affil:
          School of Art, Culture and Tourism Industry Think Tank Chinese Art Evaluation Institute, Southeast University , Nanjing, China
          School of Art, Nanjing University of Aeronautics and Astronautics , Nanjing, China
      su:
        Machine learning
        Opera
        Genetic algorithms
        Cluster analysis (Statistics)
        Musicologists
        Computer simulation
      sug:
        subj:
          Machine learning
          Opera
          Genetic algorithms
          Cluster analysis (Statistics)
          Musicologists
          Computer simulation
      keyword:
        character
        cluster analysis
        Kunqu Opera
        quantum genetic algorithm
        tone trend
      ab: Kunqu, one of the oldest forms of Chinese opera, features a unique artistic expression arising from the interplay between vocal melody and the tonal quality of its lyrics. Identifying Kunqu's character tone trend (vocal melodies derived from tonal quality of the lyrics) is critical to understanding and preserving this art form. Traditional research methods, which rely on qualitative descriptions by musicologists, have often been debated due to their subjective nature. In this study, we present a novel approach to analyze the character tone trend in Kunqu by employing computer modeling machine learning techniques. By extracting the character tone trend of Kunqu using computational modeling methods and employing machine learning techniques to apply cluster analysis on Kunqu's character tone melody, our model uncovers musical structural patterns between singing and speech, validating and refining the qualitative findings of musicologists. Furthermore, our model can automatically assess whether a piece adheres to the rhythmic norms of 'the integration of literature and music' in Kunqu, thus contributing to the digitization, creation, and preservation of this important cultural heritage.
      pubtype: Academic Journal
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    language: English
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