Intelligibility is a primary measure for the assessment of pathological speech. Traditionally, it is measured using a perceptual test, which is by definition subjective in nature. Consequently, there is a great interest in reliable, automatic and therefore objective methods. This paper presents such a method that incorporates an automatic speech recognizer (ASR) for producing features that characterize the pronunciations of a speaker and an intelligibility prediction model (IPM) for converting these features into an intelligibility score. High correlations (about 0.90) between objective and perceptual scores are obtained with a system comprising two different speech recognizers: one with traditional acoustic models relating acoustical observations to triphone states and one using phonological features as an intermediate layer between the acoustical observations and the phonetic states.
Bibliographic reference. Middag, Catherine / Nuffelen, Gwen Van / Martens, Jean-Pierre / Bodt, Marc De (2008): "Objective intelligibility assessment of pathological speakers", In INTERSPEECH-2008, 1745-1748.