JOURNAL ARTICLE

Acoustic characterization of the resonator in the Chinese transverse flute (dizi).

  • Published In: Journal of the Acoustical Society of America, 2025, v. 157, n. 5. P. 3836 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Luan, Xinmeng; Wang, Song; Scavone, Gary; Li, Zijin 3 of 3

Abstract

This article focuses on the linear acoustical behavior of the dizi, a traditional Chinese transverse flute distinguished by a hole covered with a wrinkled membrane. It presents a detailed acoustical model incorporating the dizi’s drilled toneholes, radially positioned back end-holes, membrane hole, and embouchure hole, using the transfer matrix method (TMM) and its extension with external interactions (TMMI) to predict input admittance. The study finds that TMMI more accurately models the dizi’s acoustics, particularly by accounting for mutual radiation effects among open holes, and that the membrane shifts resonance peaks to lower frequencies, reduces their magnitude, and generally improves harmonicity, though its influence varies with fingering and proximity to the membrane’s resonance frequency. Additionally, the analysis reveals that the upstream branch complicates cutoff frequency evaluation, suggesting it may be excluded to isolate tonehole lattice effects, which show distinct cutoff frequency groupings likely due to interactions between finger-hole and end-hole lattices. The modeling approach offers a scientific tool for instrument makers to assess tuning and design, with future work proposed on nonlinear membrane dynamics, improved radiation modeling, and sound synthesis applications.

Additional Information

  • Source:Journal of the Acoustical Society of America. 2025/05, Vol. 157, Issue 5, p3836
  • Document Type:Article
  • Subject Area:Music
  • Publication Date:2025
  • ISSN:0001-4966
  • DOI:10.1121/10.0036742
  • Accession Number:185593278
  • Copyright Statement:Copyright of Journal of the Acoustical Society of America is the property of American Institute of Physics and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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