[Perceptual and acoustic evaluation of hoarseness]

Validation and Classification of the 9-Item Voice Handicap Index (VHI-9i)

The international nine-item Voice Handicap Index (VHI-9i) is a clinically established short-scale version of the original VHI, quantifying the patients’ self-assessed vocal handicap. However, the current vocal impairment classification is based on percentiles. The main goals of this study were to establish test–retest reliability and a sound statistical basis for VHI-9i severity levels. Between 2009 and 2021, 17,660 consecutive cases were documented. A total of 416 test–retest pairs and 3661 unique cases with complete multidimensional voice diagnostics were statistically analyzed. Classification candidates were the overall self-assessed vocal impairment (VHIs) on a four-point Likert scale, the dysphonia severity index (DSI), the vocal extent measure (VEM), and the auditory–perceptual evaluation (GRB scale). The test–retest correlation of VHI-9i total scores was very high (r = 0.919, p < 0.01). Reliability was excellent regardless of gender or professional voice use, with negligible dependency on age. The VHIs correlated best with the VHI-9i, whereas statistical calculations proved that DSI, VEM, and GRB are unsuitable classification criteria. Based on ROC analysis, we suggest modifying the former VHI-9i severity categories as follows: 0 (healthy): 0 ≤ 7; 1 (mild): 8 ≤ 16; 2 (moderate): 17 ≤ 26; and 3 (severe): 27 ≤ 36.

Monitoring the Outcome of Phonosurgery and Vocal Exercises with Established and New Diagnostic Tools

Instrument-assisted measuring procedures expand the options within phoniatric diagnostics by quantifying the condition of the voice. The aim of this study was to examine objective treatment-associated changes of the recently developed vocal extent measure (VEM) and the established dysphonia severity index (DSI) in relation to subjective tools, i.e., self-evaluation via voice handicap index (VHI-12) and external evaluation via auditory-perceptual assessment of hoarseness (H). The findings for H (3 raters' group assessment), VHI-12, DSI, and VEM in 152 patients of both sexes (age range 16–75 years), taken before and 3 months after phonosurgery or vocal exercises, were compared and correlated. Posttherapeutically, all of the recorded parameters improved (p < 0.001). The degree of H reduced on average by 0.5, the VHI-12 score sank by 5 points, while DSI and VEM rose by 1.5 and 19, respectively. The correlations of these changes were significant but showed gradual differences between H and VHI-12 (r = 0.3), H and DSI (r = −0.3), and H and VEM (r = −0.4). We conclude that all investigated parameters are adequate to verify therapeutic outcomes but represent different dimensions of the voice. However, changes in the degree of H as gold standard were best recognized with the new VEM.

Performance of Phonatory Deviation Diagrams in Synthesized Voice Analysis

OBJECTIVE

To analyze the performance of a phonatory deviation diagram (PDD) in discriminating the presence and severity of voice deviation and the predominant voice quality of synthesized voices.

METHOD

A speech-language pathologist performed the auditory-perceptual analysis of the synthesized voice (n = 871). The PDD distribution of voice signals was analyzed according to area, quadrant, shape, and density.

RESULTS

Differences in signal distribution regarding the PDD area and quadrant were detected when differentiating the signals with and without voice deviation and with different predominant voice quality. Differences in signal distribution were found in all PDD parameters as a function of the severity of voice disorder.

CONCLUSION

The PDD area and quadrant can differentiate normal voices from deviant synthesized voices. There are differences in signal distribution in PDD area and quadrant as a function of the severity of voice disorder and the predominant voice quality. However, the PDD area and quadrant do not differentiate the signals as a function of severity of voice disorder and differentiated only the breathy and rough voices from the normal and strained voices. PDD density is able to differentiate only signals with moderate and severe deviation. PDD shape shows differences between signals with different severities of voice deviation.