Language-Independent Automatic Evaluation of Intelligibility of Chronically Hoarse Persons

Objective: Automatic intelligibility assessment using automatic speech recognition is usually language specific. In this study, a language-independent approach is proposed. It uses models that are trained with Flemish speech, and it is applied to assess chronically hoarse German speakers. The research questions are here: is it possible to construct suitable acoustic features that generalize to other languages and a speech disorder, and is the generated model for intelligibility also suitable for specific subtypes of that disorder, i. e. functional and organic dysphonia? Patients and Methods: 73 German-speaking persons with chronic hoarseness read the text ` Der Nordwind und die Sonne'. Perceptual intelligibility scores were used as ground truth during the training of an automatic model that converts speaker level acoustic measurements into intelligibility scores. Cross-validation is used to assess model performance. Results: The interrater agreement for all patients (n = 73) and for the functional and organic dysphonia subgroups (n = 45 and n = 24) are r = 0.82, r = 0.83 and r = 0.75, respectively. The automatic assessment based on phonologically based acoustic models revealed correlations between perceptual and automatic intelligibility ratings of r = 0.79 (all patients), r = 0.78 (functional dysphonia) and r = 0.80 (organic dysphonia). Conclusion: The automatic, objective measurement of intelligibility is a valuable instrument in an evidence-based clinical practice. (C) 2015 S. Karger AG, Basel