In this paper, we propose a novel boosted mixture learning (BML) framework for Gaussian mixture HMMs in speech recognition. BML is an incremental method to learn mixture models fo...
In this paper, we introduce the semantic network model (SNM), a generalization of the hidden Markov model (HMM) that uses factorization of state transition probabilities to reduce...
Stjepan Rajko, Gang Qian, Todd Ingalls, Jodi James
This paper focuses on audio-visual (using facial expression, shoulder and audio cues) classification of spontaneous affect, utilising generative models for classification (i) in t...
In the past, partial order reduction has been used successfully to combat the state explosion problem in the context of model checking for non-probabilistic systems. For both line...
Christel Baier, Pedro R. D'Argenio, Marcus Grö...
A new hierarchical nonparametric Bayesian model is proposed for the problem of multitask learning (MTL) with sequential data. Sequential data are typically modeled with a hidden M...