An Improved Glottal Flow Model Based on Seq2Seq LSTM for Simulation of Vocal Fold Vibration

Zhang, Yang; Pu, Tianmei; Zhou, Chunhua; Cai, Hongming

doi:10.1016/j.jvoice.2022.03.029

Cited by 1 publication

(1 citation statement)

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“…Based on this, a FEM solid solver computes the glottal shape in the next time-step. In a subsequent study, Zhang et al [111] improved the accuracy of the same parameter estimation by using a long short-term memory (LSTM) network and also reduced the computational time by discarding the GA optimization.…”

Section: Numerical Modeling and Machine Learningmentioning

confidence: 99%

Overview on state-of-the-art numerical modeling of the phonation process

et al. 2023

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Numerical modeling of the human phonatory process has become more and more in focus during the last two decades. The increase in computational power and the use of high-performance computation (HPC) yielded more complex models being closer to the actual fluid-structure-acoustic interaction (FSAI) within the human phonatory process. However, several different simulation approaches with varying mathematical complexity and focus on certain parts of the phonatory process exist. Currently, models are suggested based on ordinary differential equations (reduced order models) but also on partial differential equations based on continuum mechanics as e.g. the Navier–Stokes equations for the flow discretized by Finite-Volume or Finite-Element-Methods. This review will illuminate current trends and recent progress within the area. In summary, the ultimate simulation model satisfying all physiological needs and scientific opinions still has to be developed.

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Section: Numerical Modeling and Machine Learningmentioning

confidence: 99%