Abstract. An architecture for achieving word recognition and incremental learning of new words in a language processing system is presented. The architecture is based on neural ass...
In this work we present a model that uses a Dirichlet Process (DP) with a dynamic spatial constraints to approximate a non-homogeneous hidden Markov model (NHMM). The coefficient ...
Haijun Ren, Leon N. Cooper, Liang Wu, Predrag Nesk...
We describe Polynomial Conditional Random Fields for signal processing tasks. It is a hybrid model that combines the ability of Polynomial Hidden Markov models for modeling complex...