Ecological Validity of Self-Perceived Voice Quality and Acoustic Measures During Voice Assessments: An Observational...

This study investigated the ecological validity of conventional voice assessments by comparing the self-perceived voice quality and acoustic characteristics of voice production during these assessments to those in a simulated environment with varying distracting conditions and noise levels.

Forty-two university professors (26 women) participated in the study, where they were asked to produce loud connected speech by reading a 100-word text under four different conditions: a conventional assessment and three virtual classroom simulations created with 360° videos, each with different noise levels, played through a virtual reality headset and headphones. The first video depicted students paying attention in class (40 dB classroom noise); the second showed some students talking, generating moderate conversational noise (60 dB); and the third depicted students talking loudly and not paying attention (70 dB). The entire experiment was conducted in a sound-treated room, and the voice of each participant was recorded for acoustic analysis. In each condition, self-perception of voice quality (vocal effort and vocal ease), SPL, fundamental frequency, long-term average spectrum (L1-L0 ratio, alpha ratio, and the 1/5-5/8 ratio), and smooth cepstral peak prominence were measured.

Visual distraction and noise level significantly impacted both subjective and acoustic measures of voice production, as shown by numerous statistically significant differences across almost all conditions and variables examined. Specifically, all measures increased with higher levels of distraction and noise, except for the 1/5-5/8 ratio, which showed a decreasing trend.

These findings indicate that visual distraction and noise level significantly influence self-perceived and acoustic vocal characteristics and suggest that conventional assessments, typically conducted in silence and without visual distractors, may not accurately represent real-world performance, thus limiting their ecological validity.