Summary of the paper
| Title | Achieving Domain Specificity in SMT without Overt Siloing |
|---|---|
| Authors | William D. Lewis, Chris Wendt and David Bullock |
| Abstract | We examine pooling data as a method for improving Statistical MachineTranslation (SMT) quality for narrowly defined domains, such as data for aparticular company or public entity. By pooling all available data, buildinglarge SMT engines, and using domain-specific target language models, we seeboosts in quality, and can achieve the generalizability and resiliency of alarger SMT but with the precision of a domain-specific engine. |
| Language | Tools, systems, applications |
| Topics | Machine Translation, SpeechToSpeech Translation, Usability, user satisfaction, Tools, systems, applications |
Full paper  |
Achieving Domain Specificity in SMT without Overt Siloing |
| Bibtex | @InProceedings{LEWIS10.791, author = {William D. Lewis, Chris Wendt and David Bullock}, title = {Achieving Domain Specificity in SMT without Overt Siloing}, booktitle = {Proceedings of the Seventh conference on International Language Resources and Evaluation (LREC'10)}, year = {2010}, month = {may}, date = {19-21}, address = {Valletta, Malta}, editor = {Nicoletta Calzolari (Conference Chair), Khalid Choukri, Bente Maegaard, Joseph Mariani, Jan Odjik, Stelios Piperidis, Mike Rosner, Daniel Tapias}, publisher = {European Language Resources Association (ELRA)}, isbn = {2-9517408-6-7}, language = {english} } |