University of Ljubljana System for Interspeech 2011

The paper presents our efforts in the Interspeech 2011 Speaker State Challenge. Both systems, for the Intoxication and the Sleepiness Sub-Challenge, are based on a Universal Back-ground Model (UBM) in a form of a Hidden Markov Model (HMM), and the Maximum A Posteriori (MAP) adaptation. With the combination of our HMM-UBM-MAP derived super-vectors and selected statistical functionals from the baseline fea-ture set, we were able to surpass the baseline system in both sub-challenges. By employing majority voting fusion of best systems we were able to further improve the performance. In the Intoxication Sub-Challenge our best result on the test set is 67.46%, and in the Sleepiness Sub-Challenge 71.28%