Summary of the paper

Title Towards Improving English-Latvian Translation: A System Comparison and a New Rescoring Feature
Authors Maxim Khalilov, José A. R. Fonollosa, Inguna Skadina, Edgars Brālītis and Lauma Pretkalnina
Abstract Translation into the languages with relatively free word order has received a lot less attention than translation into fixed word order languages (English), or into analytical languages (Chinese). At the same time this translation task is found among the most difficult challenges for machine translation (MT), and intuitively it seems that there is some space in improvement intending to reflect the free word order structure of the target language. This paper presents a comparative study of two alternative approaches to statistical machine translation (SMT) and their application to a task of English-to-Latvian translation. Furthermore, a novel feature intending to reflect the relatively free word order scheme of the Latvian language is proposed and successfully applied on the n-best list rescoring step. Moving beyond classical automatic scores of translation quality that are classically presented in MT research papers, we contribute presenting a manual error analysis of MT systems output that helps to shed light on advantages and disadvantages of the SMT systems under consideration.
Topics Machine Translation, SpeechToSpeech Translation, Language modelling
Full paper Towards Improving English-Latvian Translation: A System Comparison and a New Rescoring Feature
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Bibtex @InProceedings{KHALILOV10.228,
  author = {Maxim Khalilov and José A. R. Fonollosa and Inguna Skadina and Edgars Brālītis and Lauma Pretkalnina},
  title = {Towards Improving English-Latvian Translation: A System Comparison and a New Rescoring Feature},
  booktitle = {Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC'10)},
  year = {2010},
  month = {may},
  date = {19-21},
  address = {Valletta, Malta},
  editor = {Nicoletta Calzolari (Conference Chair) and Khalid Choukri and Bente Maegaard and Joseph Mariani and Jan Odijk and Stelios Piperidis and Mike Rosner and Daniel Tapias},
  publisher = {European Language Resources Association (ELRA)},
  isbn = {2-9517408-6-7},
  language = {english}
 }
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