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Classification and Selection of Translation Candidates for Parallel Corpora Alignment

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Progress in Artificial Intelligence (EPIA 2015)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9273))

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Abstract

By incorporating human feedback in parallel corpora alignment and term translation extraction tasks, and by using all human validated term translation pairs that have been marked as correct, the alignment precision, term translation extraction quality and a bunch of closely correlated tasks improve. Moreover, such a labelled lexicon with entries tagged for correctness enables bilingual learning. From this perspective, we present experiments on automatic classification of translation candidates extracted from aligned parallel corpora. For this purpose, we train SVM based classifiers for three language pairs, English-Portuguese (EN-PT), English-French (EN-FR) and French-Portuguese (FR-PT). The approach enabled micro f-measure classification rates of 95.96%, 75.04% and 65.87% respectively, for the EN-PT, EN-FR and FR-PT language pairs.

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Author information

Authors and Affiliations

  1. NOVA Laboratory for Computer Science and Informatics (NOVA LINCS), Faculdade de Ciências e Tecnologia, Universidade Nova de Lisboa, 2829-516, Caparica, Portugal

    K. M. Kavitha, Luís Gomes, José Aires & José Gabriel P. Lopes

  2. ISTRION BOX-Translation & Revision, Lda., Parkurbis, 6200-865, Covilhã, Portugal

    Luís Gomes, José Aires & José Gabriel P. Lopes

  3. Department of Computer Applications, St. Joseph Engineering College, Vamanjoor, Mangaluru, 575 028, India

    K. M. Kavitha

Authors
  1. K. M. Kavitha
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  2. Luís Gomes
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  3. José Aires
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  4. José Gabriel P. Lopes
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Corresponding author

Correspondence to K. M. Kavitha .

Editor information

Editors and Affiliations

  1. ISEC - Coimbra Institute of Engineering, Polytechnic Institute of Coimbra, Coimbra, Portugal

    Francisco Pereira

  2. CIUSC, Department of Informatics Engineering, University of Coimbra, Coimbra, Portugal

    Penousal Machado

  3. CIUSC, Department of Informatics Engineering, University of Coimbra, Coimbra, Portugal

    Ernesto Costa

  4. CIUSC, Department of Informatics Engineering, University of Coimbra, Coimbra, Portugal

    Amílcar Cardoso

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Kavitha, K.M., Gomes, L., Aires, J., Lopes, J.G.P. (2015). Classification and Selection of Translation Candidates for Parallel Corpora Alignment. In: Pereira, F., Machado, P., Costa, E., Cardoso, A. (eds) Progress in Artificial Intelligence. EPIA 2015. Lecture Notes in Computer Science(), vol 9273. Springer, Cham. https://doi.org/10.1007/978-3-319-23485-4_73

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  • DOI: https://doi.org/10.1007/978-3-319-23485-4_73

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-23484-7

  • Online ISBN: 978-3-319-23485-4

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