This paper introduces a general framework for the use of translation probabilities in cross-language information retrieval based on the notion that information retrieval fundament...
This paper describes a shallow parsing formalism aiming at machine translation between closely related languages. The formalism allows to write grammar rules helping to (partially...
Selecting the right word translation among several options in the lexicon is a core problem for machine translation. We present a novel approach to this problem that can be traine...
Statistical models in machine translation exhibit spurious ambiguity. That is, the probability of an output string is split among many distinct derivations (e.g., trees or segment...
Training statistical models to detect nonnative sentences requires a large corpus of non-native writing samples, which is often not readily available. This paper examines the exte...