Advertisement

Machine Translation

, Volume 17, Issue 2, pp 77–98 | Cite as

Trans Type: Development-Evaluation Cycles to Boost Translator's Productivity

  • Philippe Langlais
  • Guy Lapalme
Article

Abstract

We present TransType: a new approach to Machine-Aided Translation in which the human translator maintains control of the translation process while being helped by real-time completions proposed by a statistical translation engine. The TransType approach is first presented through a series of prototypes that illustrate their underlying translation model and graphical interface. The results of two rounds of in situ evaluation of TransType prototypes are discussed followed by a set of lessons learned in these experiments. It will be shown that this approach is valued by translators but given the short time allotted for the evaluation, translators were not able to quantitatively increase their productivity. TransType is compared with other approaches and new perspectives are elaborated for a new version being developed in the context of a Fifth Framework European Community Project.

machine-assisted human translation interactive machine translation target-text mediation word completion statistical translation models statistical language models 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Blanchon, H.: 1991, ‘Problèmes de désambiguisation interactive et TAO personelle’ [Problems with interactive disambiguation and personal CAT], in A. Clas and H. Safar (eds), L'environnement traductionnel: La station de travail du traducteur de l'an 2001, Presses de l'Université du Québec, Sainte-Foy (Québec), pp. 31–48.Google Scholar
  2. Brousseau, J., C. Drouin, G. Foster, P. Isabelle, R. Kuhn, Y. Normandin, and P. Plamondon: 1995, ‘French Speech Recognition in an Automatic Dictation System for Translators: The Transtalk Project’, in 4th European Conference on Speech, Communication and Technology (Eurospeech 95), Madrid, pp. 193–196.Google Scholar
  3. Brown, P. F., S. A. Della Pietra, V. J. Della Pietra, and R. L. Mercer: 1993, ‘The Mathematics of Machine Translation: Parameter Estimation’, Computational Linguistics 19, 263–312.Google Scholar
  4. Brown, R. D. and S. Nirenburg: 1990, ‘Human-Computer Interaction for Semantic Disambiguation’, in COLING-90: Papers presented to the 13th International Conference on Computational Linguistics, Helsinki, Finland, Vol. 3, pp. 42–47.Google Scholar
  5. Chandioux, J.: 1989, ‘Météo: 100 Million Words Later’, in D. L. Hammond (ed.), American Translators Association Conference 1989: Coming of Age, Learned Information, Medford, NJ, pp. 449–453.Google Scholar
  6. Darragh, J. J. and I. H. Witten: 1992, The Reactive Keyboard, Cambridge University Press, Cambridge.Google Scholar
  7. Foster, G.: 2000, ‘Incorporating Position Information into a Maximum Entropy/Minimum Divergence Translation Model’, in 4th Computational Natural Language Learning Workshop, Lisbon, Portugal, pp. 37–52.Google Scholar
  8. Foster, G., P. Isabelle, and P. Plamondon: 1997, ‘Target-Text Mediated Interactive Maching Translation’, Machine Translation 12, 175–194.CrossRefGoogle Scholar
  9. Jelinek, F.: 1990, ‘Self-organized Language Modeling for Speech Recognition’, in A. Waibel and K. Lee (eds), Readings in Speech Recognition, San Mateo, California: Morgan Kaufmann, pp. 450–506.Google Scholar
  10. Kay, M.: 1973, ‘The MIND System’, in R. Rustin (ed.), Natural Language Processing, Algorithmics Press, New York, pp. 155–188.Google Scholar
  11. Kay, M.: 1998, ‘Machine Translation: The Disappointing Past and Present’, in R. A. Cole, J. Mariani, H. Uszkoreit, G. B. Varile, A. Zaenen and A. Zampolli (eds), Survey of the State of the Art in Human Language Technology, Cambridge University Press, Cambridge, Chap. 8.2.Google Scholar
  12. Langlais, P. and G. Foster: 2000, ‘Using Context-Dependent Interpolation to Combine Statistical Language and Translation Models for Interactive Machine Translation’, in RIAO 2000: Content-Based Multimedia Information Access, Paris, pp. 507–518.Google Scholar
  13. Langlais, P., G. Foster, and G. Lapalme: 2000a, ‘Unit Completion for a Computer-Aided Translation Typing System’, Machine Translation 15, 267–294.CrossRefGoogle Scholar
  14. Langlais, P., G. Foster, and G. Lapalme: 2001a, ‘Integration Bilingual Lexicons in Probabilistic Translation Assistant’, in MT Summit VIII: Machine Translation in the Information Age, Santiago de Compostela, Spain, pp. 197–202.Google Scholar
  15. Langlais, P., G. Lapalme, and S. Sauvé: 2001b, ‘User Interface Aspects of a Translation Typing System’, in E. Stroulia and S. Matwin (eds.), Advances in Artificial Intelligence, Springer, Berlin, pp. 246–256.Google Scholar
  16. Langlais, P., S. Sauvé, G. Foster, E. Macklovitch, and G. Lapalme: 2000b, ‘Evaluation of Trans-Type, a Computer-Aided Translation Typing System: A Comparison of Theoretical-and User-Oriented Evaluation Procedures’, in Second International Conference on Language Resources and Evaluation (LREC), Athens, Greece, pp. 641–648.Google Scholar
  17. Maruyama, H., H. Watanabe, and S. Ogino: 1990, ‘An Interactive Japanese Parser for Machine Translation’, in COLING-90: Papers presented to the 13th International Conference on Computational Linguistics, Helsinki, Finland, Vol. 2, pp. 257–262.Google Scholar
  18. Miller, G. A.: 1956, ‘The Magical Number Seven, Plus or Minus Two: Some Limits on our Capacity for Processing Information’, Psychological Review 63, 81–97.CrossRefGoogle Scholar
  19. Sema Spain, Computer Science Department RWTH Aachen — University of Technology, Instituto Tecnológico de Informática, Universidad Politécnica de Valencia, RALI Laboratory — University of Montreal, Celer Soluciones, Société Gamma, and Xerox Research Centre Europe: 2002, ‘Transtype2 — Computer Assisted Translation Project funded by the European Commission under the IST Programme (IST-2001-32091)'. http://tt2.sema.es/.Google Scholar
  20. TranslatrosWorkbench98: 1998, ‘Trados Translator's Workbench 2, Product Description’, www.trados.com/workbench/index.html.Google Scholar
  21. Whitelock, P. J., M. M. Wood, B. J. Chandler, N. Holden, and H. J. Horsfall: 1986, ‘Strategies for Interactive Machine Translation: The Experience and Implications of the UMIST Japanese Project’, in 11th International Conference on Computational Linguistics: Proceedings of Coling’ 86, Bonn, West Germany, pp. 329–334.Google Scholar
  22. WorldQ: 2001, ‘Product Description’, www.wordq.com.Google Scholar

Copyright information

© Kluwer Academic Publishers 2002

Authors and Affiliations

  • Philippe Langlais
    • 1
  • Guy Lapalme
    • 1
  1. 1.RALI/DIRO – Université de Montréalsuccursale Centre-villeCanada

Personalised recommendations