Detecting Hodo and Zu in Bunraku Nonverbal Communication using Hilbert-Huang Transform

Nonverbal communication relies on human actions to convey information through signals. In Bunraku puppetry performance, a UNESCO Intangible Cultural Heritage, three puppeteers manipulate a single puppet using the rhythmic structure of "Hodo" and "Zu". The puppeteer master embeds cues, "Hodo" and "Zu", into the puppet's movements, guiding coordination. However, the mechanics of these cues remain unclear. Despite this, shared gestures and rhythms enable seamless collaboration. This paper proposes a signal analysis framework using Principal Component Analysis and Hilbert-Huang Transform to investigate how puppeteers achieve nonverbal communication, synchronizing movements and rhythmic variations to manipulate the puppet with natural fluidity. The correlation analysis using Procrustes Analysis, Mutual Information, and Canonical Correlation Analysis, along with the examples identified through this method, all meet statistical significance across these three validation approaches, confirming the effectiveness of our method.

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Publication Details

Journal
The Journal of the Society for Art and Science
Published
2025-06-30
DOI
https://doi.org/10.3756/artsci.24.7_1
Primary Topic
Speech and Audio Processing
Type
article
Field-Weighted Citation Impact
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article

Detecting Hodo and Zu in Bunraku Nonverbal Communication using Hilbert-Huang Transform

Xunan LIU, Ran Dong
The Journal of the Society for Art and Science
Speech and Audio Processing
article

Detecting Hodo and Zu in Bunraku Nonverbal Communication using Hilbert-Huang Transform

Xunan LIU, Ran Dong
article en

Abstract

Nonverbal communication relies on human actions to convey information through signals. In Bunraku puppetry performance, a UNESCO Intangible Cultural Heritage, three puppeteers manipulate a single puppet using the rhythmic structure of "Hodo" and "Zu". The puppeteer master embeds cues, "Hodo" and "Zu", into the puppet's movements, guiding coordination. However, the mechanics of these cues remain unclear. Despite this, shared gestures and rhythms enable seamless collaboration. This paper proposes a signal analysis framework using Principal Component Analysis and Hilbert-Huang Transform to investigate how puppeteers achieve nonverbal communication, synchronizing movements and rhythmic variations to manipulate the puppet with natural fluidity. The correlation analysis using Procrustes Analysis, Mutual Information, and Canonical Correlation Analysis, along with the examples identified through this method, all meet statistical significance across these three validation approaches, confirming the effectiveness of our method.

The Journal of the Society for Art and ScienceVol. 24(2)
Nagoya University of Commerce and Business (JP), University of Tsukuba (JP), Chukyo University (JP)
Reduced inequalities
Openalex Percentile: Top 78%
Speech and Audio Processing
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Detecting Hodo and Zu in Bunraku Nonverbal Communication using Hilbert-Huang Transform — Xunan LIU, Ran Dong · The Journal of the Society for Art and Science (2025) | TGRS Research Map | TGRS