English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

So far, several physical models have been proposed for the study of vocalfold oscillations during phonation. The parameters of these models, such asvocal fold elasticity, resistance, etc. are traditionally determined throughthe observation and measurement of the vocal fold vibrations in the larynx.Since such direct measurements tend to be the most accurate, the traditionalpractice has been to set the parameter values of these models based onmeasurements that are averaged across an ensemble of human subjects. However,the direct measurement process is hard to revise outside of clinical settings.In many cases, especially in pathological ones, the properties of the vocalfolds often deviate from their generic values---sometimes asymmetricallywherein the characteristics of the two vocal folds differ for the sameindividual. In such cases, it is desirable to find a more scalable way toadjust the model parameters on a case by case basis. In this paper, we presenta novel and alternate way to determine vocal fold model parameters from thespeech signal. We focus on an asymmetric model and show that for such models,differences in estimated parameters can be successfully used to discriminatebetween voices that are characteristic of different underlying vocal foldpathologies.

Speech-Based Parameter Estimation of an Asymmetric Vocal Fold Oscillation Model and Its Application in Discriminating Vocal Fold Pathologies