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<?xml version="1.0" standalone="yes"?> <Paper uid="W00-1312"> <Title>Cross-lingual Information Retrieval using Hidden Markov Models</Title> <Section position="1" start_page="0" end_page="0" type="abstr"> <SectionTitle> Abstract </SectionTitle> <Paragraph position="0"> This paper presents empirical results in cross-lingual information retrieval using English queries to access Chinese documents (TREC-5 and TREC-6) and Spanish documents (TREC-4). Since our interest is in languages where resources may be minimal, we use an integrated probabilistic model that requires only a bilingual dictionary as a resource. We explore how a combined probability model of term translation and retrieval can reduce the effect of translation ambiguity. In addition, we estimate an upper bound on performance, if translation ambiguity were a solved problem. We also measure performance as a function of bilingual dictionary size.</Paragraph> </Section> class="xml-element"></Paper>