Automatic detection of voice onset time in dysarthric speech

Although a number of speech disorders reflect varying involvement of brain areas, recently published automatic speech analyses have primarily been limited to hypokinetic dysarthria in Parkinson´s disease (PD). Therefore, the aim of the present study was to provide an automatic algorithm suitable for the assessment of voice onset time (VOT) in various dysarthria types. Twenty-four PD participants with hypokinetic dysarthria and 40 Huntington´s disease (HD) subjects with hyperkinetic dysarthria were included. These two types of dysarthria were selected in the design of a robust algorithm as they contain most of the dysarthric patterns found among all dysarthria subtypes. For a 10 ms threshold, the proposed algorithm reached approximately 90% accuracy in PD speakers and 80% accuracy in HD speakers. The accuracy of 80% obtained in HD was superior to the performance of 55% achieved by a previous algorithm designed particularly for hypokinetic dysarthria in PD.