In this paper, we propose a new Bayesian model for fully unsupervised word segmentation and an efficient blocked Gibbs sampler combined with dynamic programming for inference. Our...
In this paper, with a belief that a language model that embraces a larger context provides better prediction ability, we present two extensions to standard n-gram language models ...
This is a system demo for a set of tools for translating texts between multiple languages in real time with high quality. The translation works on restricted languages, and is bas...
We show how features can easily be added to standard generative models for unsupervised learning, without requiring complex new training methods. In particular, each component mul...
Taylor Berg-Kirkpatrick, Alexandre Bouchard-C&ocir...
Little is known about the impact of politeness in online communities. This project combines deductive and inductive approaches to automatically model linguistic politeness in onli...