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Human Voice as a Measure of Mental Load Level
Stanislas Boyer1, Pierre-Vincent Paubel1, Robert Ruiz2
1Cognition, Languages, Language, Ergonomics-Work & Cognition Laboratory (CLLE-LTC), University of Toulouse and Centre National de la Recherche Scientifique, France.
Journal of Speech, Language, and Hearing Research : JSLHR
|November 2, 2018
Summary
Voice acoustic parameters can effectively estimate mental load. Specific vocal features predict cognitive task difficulty, offering a non-invasive method for monitoring mental workload.
Area of Science:
- Cognitive Psychology
- Acoustic Phonetics
- Human-Computer Interaction
Background:
- Real-time mental load detection is crucial for performance enhancement, especially in high-risk professions like aviation.
- Current methods for monitoring mental workload face significant challenges in implementation and real-time analysis.
Purpose of the Study:
- To identify reliable and efficient acoustic parameters in human voice for estimating mental load.
- To explore the potential of vocal analysis as a non-invasive tool for workload assessment.
Main Methods:
- Recorded voices of 32 participants during a word list recall cognitive task with 7 difficulty levels.
- Manipulated task difficulty by varying the number of words (1-7) to recall.
- Simultaneously recorded evoked pupillary response as a proxy for mental load.
Main Results:
- Both classic (fundamental frequency, standard deviation) and novel acoustic features (frequency modulation, amplitude variation) predicted memory load.
- Significant variations in acoustic parameters were observed beyond a recall threshold of 3-5 words, coinciding with performance decline.
Conclusions:
- Certain acoustic parameters of the human voice show promise for accurately detecting mental load levels.
- Vocal analysis offers a potentially efficient and appropriate method for real-time mental workload monitoring.
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