Does it Groove or Does it Stumble - Automatic Classification of Alcoholic Intoxication Using Prosodic Features

摘要

This paper studies how prosodic features can help in the automatic detection of alcoholic intoxication. We compute features that have recently been proposed to model speech rhythm such as the pair-wise variability index for consonantal and vocalic segments (PVI) and study their aptness for the task. Further, we use a large prosodic feature vector modelling the usual candidates - pitch, intensity, and duration - and apply it onto different units such as words, syllables and stressed syllables to create generalizations of the rhythm features mentioned. The results show that the prosodic features computed are suitable for detecting alcoholic intoxication and add complementary information to state-of-the-art features. The database is the intoxication database provided by the organizers of the 2011 Inter-speech Speaker State Challenge.