A self-adaptive Hidden Markov Model (SA-HMM) based framework is proposed for behavior recognition in this paper. In this model, if an unknown sequence cannot be classified into an...
Hidden Markov Models (HMMs) are important tools for modeling sequence data. However, they are restricted to discrete latent states, and are largely restricted to Gaussian and disc...
Le Song, Sajid M. Siddiqi, Geoffrey J. Gordon, Ale...
Identifying effective tutorial strategies is a key problem for tutorial dialogue systems research. Ongoing work in human-human tutorial dialogue continues to reveal the complex phe...
Kristy Elizabeth Boyer, Eunyoung Ha, Michael D. Wa...
— This paper proposes a Hidden Markov Model (HMM) based approach to generate human-like movements for humanoid robots. Given human motion capture data for a class of movements, p...
Abstract. We propose a semantic tagger that provides high level concept information for phrases in clinical documents. It delineates such information from the statements written by...