TREC-7 CLIR using a Probabilistic Translation Model

In this report, we describe the approach we used in TREC-7 Cross-Language IR (CLIR) track. The approach is based on a probabilistic translation model estimated from a parallel training corpus (Canadian HANSARD). The problem of translating a query from a language to another (between French and English) becomes the problem of determining the most probable words that may appear in the translation of the query. In this paper, we will describe the principle of building the probabilistic model, and the runs we submitted using the model as a translation tool.