We pose the development of cognitively plausible models of human language processing as a challenge for computational linguistics. Existing models can only deal with isolated phen...
We propose a new hierarchical Bayesian n-gram model of natural languages. Our model makes use of a generalization of the commonly used Dirichlet distributions called Pitman-Yor pr...
In this paper we propose a novel statistical language model to capture long-range semantic dependencies. Specifically, we apply the concept of semantic composition to the problem ...
To formalize a software process, its important aspects must be extracted as a model. Many processes are used repeatedly, and the ability to automate a process is also desired. One...
We present a joint morphological-lexical language model (JMLLM) for use in statistical machine translation (SMT) of language pairs where one or both of the languages are morpholog...