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Cross-lingual information retrieval is a challenging task in the absence ofaligned parallel corpora. In this paper, we address this problem by consideringtopically aligned corpora designed for evaluating an IR setup. To emphasize, weneither use any sentence-aligned corpora or document-aligned corpora, nor do weuse any language specific resources such as dictionary, thesaurus, or grammarrules. Instead, we use an embedding into a common space and learn wordcorrespondences directly from there. We test our proposed approach forbilingual IR on standard FIRE datasets for Bangla, Hindi and English. Theproposed method is superior to the state-of-the-art method not only for IRevaluation measures but also in terms of time requirements. We extend ourmethod successfully to the trilingual setting.

Learning Multilingual Embeddings for Cross-Lingual Information Retrieval in the Presence of Topically Aligned Corpora