Automatic Evaluation of Voice Quality Using Text-Based Laryngograph Measurements and Prosodic Analysis

Abstract

Due to low intra- and interrater reliability, perceptual voice evaluation should be supported by objective, automatic methods. In this study, text-based, computer-aided prosodic analysis and measurements of connected speech were combined in order to model perceptual evaluation of the German Roughness-Breathiness-Hoarseness (RBH) scheme. 58 connected speech samples (43 women and 15 men; 48.7 ± 17.8 years) containing the German version of the text “The North Wind and the Sun” were evaluated perceptually by 19 speech and voice therapy students according to the RBH scale. For the human-machine correlation, Support Vector Regression with measurements of the vocal fold cycle irregularities (CFx) and the closed phases of vocal fold vibration (CQx) of the Laryngograph and 33 features from a prosodic analysis module were used to model the listeners' ratings. The best human-machine results for roughness were obtained from a combination of six prosodic features and CFx (r = 0.71, ρ = 0.57). These correlations were approximately the same as the interrater agreement among human raters (r = 0.65, ρ = 0.61). CQx was one of the substantial features of the hoarseness model. For hoarseness and breathiness, the human-machine agreement was substantially lower. Nevertheless, the automatic analysis method can serve as the basis for a meaningful objective support for perceptual analysis.

Feature Space Visualization with Spatial Similarity Maps for Pathological Speech Data

“…Originally, there were 95 local prosodic features computed for each word position. After several studies on voice and speech assessment, however, a relevant core set of 33 features had been defined for further processing [16], including statistics about pauses, energy, duration and F0. The 33 local features per word were then averaged with respect to different conditions, for example over all words, over all nouns, or over all verbs and nouns.…”