Title |
A Quality-based Active Sample Selection Strategy for Statistical Machine Translation |
Authors |
Varvara Logacheva and Lucia Specia |
Abstract |
This paper presents a new active learning technique for machine translation based on quality estimation of automatically translated sentences. It uses an error-driven strategy, i.e., it assumes that the more errors an automatically translated sentence contains, the more informative it is for the translation system. Our approach is based on a quality estimation technique which involves a wider range of features of the source text, automatic translation, and machine translation system compared to previous work. In addition, we enhance the machine translation system training data with post-edited machine translations of the sentences selected, instead of simulating this using previously created reference translations. We found that re-training systems with additional post-edited data yields higher quality translations regardless of the selection strategy used. We relate this to the fact that post-editions tend to be closer to source sentences as compared to references, making the rule extraction process more reliable. |
Topics |
Evaluation Methodologies, Statistical and Machine Learning Methods |
Full paper |
A Quality-based Active Sample Selection Strategy for Statistical Machine Translation |
Bibtex |
@InProceedings{LOGACHEVA14.658,
author = {Varvara Logacheva and Lucia Specia}, title = {A Quality-based Active Sample Selection Strategy for Statistical Machine Translation}, booktitle = {Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14)}, year = {2014}, month = {may}, date = {26-31}, address = {Reykjavik, Iceland}, editor = {Nicoletta Calzolari (Conference Chair) and Khalid Choukri and Thierry Declerck and Hrafn Loftsson and Bente Maegaard and Joseph Mariani and Asuncion Moreno and Jan Odijk and Stelios Piperidis}, publisher = {European Language Resources Association (ELRA)}, isbn = {978-2-9517408-8-4}, language = {english} } |