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Author Spotlight: Investigating the Impact of Emotional Prosodies on Voice Recognition and Perception

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Vocal Change Patterns During a Teaching Day: Inter- and Intra-subject Variability.

Angélique Remacle¹, Maëva Garnier¹, Silvain Gerber¹

¹CNRS, GIPSA-lab, 11 rue des Mathématiques, Saint Martin d'Hères Cedex, France; University Grenoble-Alpes, Grenoble, France.

Journal of Voice : Official Journal of the Voice Foundation

|May 13, 2017

Summary

Teacher voice patterns change throughout the workday, with acoustic measures revealing distinct individual variations. Understanding these voice changes is key for targeted prevention and treatment strategies.

Keywords:

Acoustic analysis Teachers Vocal fatigue Vocal hyperfunction Vocal loading

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Area of Science:

Speech and Hearing Science
Occupational Health
Acoustic Phonetics

Background:

Teachers experience significant vocal load during their workday.
Voice changes in occupational settings are common but understudied.
Individual variability in vocal responses to occupational stress is expected.

Purpose of the Study:

To characterize mean voice changes in female teachers over a typical workday.
To analyze inter- and intra-subject variability in vocal parameters.
To establish a typology of voice patterns based on workday acoustic changes.

Main Methods:

Acoustic analysis of sustained vowels was performed on 22 female teachers.
Measurements included fundamental frequency (F0), harmonics-to-noise ratio (HNR), jitter, and shimmer.
Data were collected at the beginning and end of the workday, across three school year time points.

Main Results:

Group analysis revealed significant increases in F0 and HNR, and decreases in jitter and shimmer during the workday.
Substantial inter- and intra-subject variability in vocal parameters was observed.
Three distinct voice patterns emerged: adaptive, hyperfunctional, and fatigue/inflammation-related.

Conclusions:

Vocal patterns in teachers exhibit significant individual differences throughout the workday.
Recognizing diverse vocal responses is crucial for developing personalized voice care strategies.
Tailored prevention and treatment methods are needed based on identified voice patterns.