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Transliteration Equivalence Using Canonical Correlation Analysis

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Advances in Information Retrieval (ECIR 2010)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 5993))

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Abstract

We address the problem of Transliteration Equivalence, i.e. determining whether a pair of words in two different languages (e.g. Auden, ऑडेन) are name transliterations or not. This problem is at the heart of Mining Name Transliterations (MINT) from various sources of multilingual text data including parallel, comparable, and non-comparable corpora and multilingual news streams. MINT is useful in several cross-language tasks including Cross-Language Information Retrieval (CLIR), Machine Translation (MT), and Cross-Language Named Entity Retrieval. We propose a novel approach to Transliteration Equivalence using language-neutral representations of names. The key idea is to consider name transliterations in two languages as two views of the same semantic object and compute a low-dimensional common feature space using Canonical Correlation Analysis (CCA). Similarity of the names in the common feature space forms the basis for classifying a pair of names as transliterations. We show that our approach outperforms state-of-the-art baselines in the CLIR task for Hindi-English (3 collections) and Tamil-English (2 collections).

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Author information

Authors and Affiliations

  1. Microsoft Research, India

    Raghavendra Udupa

  2. Indian Institute of Technology, Bombay

    Mitesh M. Khapra

Authors
  1. Raghavendra Udupa
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  2. Mitesh M. Khapra
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Editor information

Editors and Affiliations

  1. Adaptive Information Cluster, Dublin City University, Dublin, 9, Ireland

    Cathal Gurrin

  2. The Open University, Walton Hall, MK7 6HF, Milton Keynes, UK

    Yulan He

  3. Microsoft Research Ltd, 7 JJ Thomson Avenue, CB3 0FB, Cambridge, UK

    Gabriella Kazai

  4. Department of Computer Science, University of Essex, Wivenhoe Park, CO4 3SQ, Colchester, UK

    Udo Kruschwitz

  5. The Open University, Walton Hall, Milton Keynes, UK

    Suzanne Little

  6. University of London, London, UK

    Thomas Roelleke

  7. Knowledge Media Institute, The Open University, MK7 6AA, Milton Keynes, UK

    Stefan Rüger

  8. Department of Computing Science, University of Glasgow, 17 Lilybank Gardens, G12 8QQ, Glasgow, UK

    Keith van Rijsbergen

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Udupa, R., Khapra, M.M. (2010). Transliteration Equivalence Using Canonical Correlation Analysis. In: Gurrin, C., et al. Advances in Information Retrieval. ECIR 2010. Lecture Notes in Computer Science, vol 5993. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12275-0_10

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  • DOI: https://doi.org/10.1007/978-3-642-12275-0_10

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-12274-3

  • Online ISBN: 978-3-642-12275-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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