Hierarchical sub-sentential alignment with anymalign

Adrien Lardilleux, François Yvon, Yves Lepage

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Citations (Scopus)

Abstract

We present a sub-sentential alignment algorithm that relies on association scores between words or phrases. This algorithm is inspired by previous work on alignment by recursive binary segmentation and on document clustering. We evaluate the resulting alignments on machine translation tasks and show that we can obtain state-of-the-art results, with gains up to more than 4 BLEU points compared to previous work, with a method that is simple, independent of the size of the corpus to be aligned, and directly computes symmetric alignments. This work also provides new insights regarding the use of "heuristic" alignment scores in statistical machine translation.

Original languageEnglish
Title of host publicationProceedings of the 16th Annual Conference of the European Association for Machine Translation, EAMT 2012
PublisherEuropean Association for Machine Translation
Pages279-286
Number of pages8
Publication statusPublished - 2012
Event16th Annual Conference of the European Association for Machine Translation, EAMT 2012 - Trento, Italy
Duration: 2012 May 282012 May 30

Other

Other16th Annual Conference of the European Association for Machine Translation, EAMT 2012
CountryItaly
CityTrento
Period12/5/2812/5/30

    Fingerprint

ASJC Scopus subject areas

  • Language and Linguistics
  • Human-Computer Interaction
  • Software

Cite this

Lardilleux, A., Yvon, F., & Lepage, Y. (2012). Hierarchical sub-sentential alignment with anymalign. In Proceedings of the 16th Annual Conference of the European Association for Machine Translation, EAMT 2012 (pp. 279-286). European Association for Machine Translation.