The Relationship Between Physiological Mechanisms and the Self-Perception of Vocal Effort

Abstract

Purpose This study aimed to examine the relationship between a large set of hypothesized physiological measures of vocal effort and self-ratings of vocal effort. Method Twenty-six healthy adults modulated speech rate and vocal effort during repetitions of the utterance /ifi/, followed by self-perceptual ratings of vocal effort on a visual analog scale. Physiological measures included (a) intrinsic laryngeal tension via kinematic stiffness ratios determined from high-speed laryngoscopy, (b) extrinsic suprahyoid and infrahyoid laryngeal tension via normalized percent activations and durations derived from surface electromyography, (c) supraglottal compression via expert visual-perceptual ratings, and (d) subglottal pressure via magnitude of neck surface vibrations from an accelerometer signal. Results Individual statistical models revealed that all of the physiological predictors, except for kinematic stiffness ratios, were significantly predictive of self-ratings of vocal effort. However, a combined regression model analysis yielded only 3 significant predictors: subglottal pressure, mediolateral supraglottal compression, and the normalized percent activation of the suprahyoid muscles (adjusted R ² = .60). Conclusions Vocal effort manifests as increases in specific laryngeal physiological measures. Further work is needed to examine these measures in combination with other contributing factors, as well as in speakers with dysphonia.

Figure 1.

Example of surface EMG sensor placement on the submandibular region (suprahyoid) and anterior neck (infrahyoid).

Figure 2.

(a) View of the vocal folds under flexible laryngoscopy. The glottic angle has been marked from the anterior commissure to the vocal processes. (b) Raw vocal fold angles with smoothed data overlay. Maximum angle (circle), maximum angular velocity (square), and the range of 20%–80% of the maximum angle are identified.

Figure A1.

The upper panel shows a filtered accelerometer signal that was used to determine the onset and offset of voicing for each /ifi/ production, delineated by a solid dark line. The dashed line (- -) represents a time period set to 250 ms prior to each phonation onset. Segment 1 and Segment 2 are the two /ifi/ segments that include the voicing segment plus the prephonatory segment. The lower panel is an example of the sEMG signal acquired from the sensor located at the left infrahyoid location. In this example, the analysis of Segment 1 and Segment 2 revealed a mean normalized activation amplitude of 3% and mean duration of activation of 100%.

Figure A2.

(a) Laryngoscopy image with glottic midpoint identified. (b) Laryngoscopy image with glottic space identified (circles) for algorithm pixel differentiation. (c) Regression lines (- -) placed along the vocal fold edges to determine the glottic angle.

Figure A3.

Raw vocal fold angles with low and high envelopes. Arrows indicate point of convergence of the envelopes. The raw angles were used within the space between the arrows and the low angles were used outside the arrows for further processing.

Figure A4.

Image of the smoothed angle data. The maximum abductory angle and the maximum angular velocity have been determined in the range of 20%–80%, with consideration of the filter window.

Figure A5.

Schematic of the interactive screen during data processing. The user was able to see the videoendoscopic image, microphone and accelerometer signals, raw angle waveform (here, the angles have been smoothed during the /f/ segment), and the angular velocity waveform derived from the processed angle data.