TY - GEN
T1 - Two phase evaluation for selecting machine translation services
AU - Shi, Chunqi
AU - Lin, Donghui
AU - Shimada, Masahiko
AU - Ishida, Toru
N1 - Funding Information:
This research was partially supported by Service Science, Solutions and Foundation Integrated Research Program from JST RISTEX.
PY - 2012
Y1 - 2012
N2 - An increased number of machine translation services are now available. Unfortunately, none of them can provide adequate translation quality for all input sources. This forces the user to select from among the services according to his needs. However, it is tedious and time consuming to perform this manual selection. Our solution, proposed here, is an automatic mechanism that can select the most appropriate machine translation service. Although evaluation methods are available, such as BLEU, NIST, WER, etc., their evaluation results are not unanimous regardless of the translation sources. We proposed a two-phase architecture for selecting translation services. The first phase uses a data-driven classification to allow the most appropriate evaluation method to be selected according to each translation source. The second phase selects the most appropriate machine translation result by the selected evaluation method. We describe the architecture, detail the algorithm, and construct a prototype. Tests show that the proposal yields better translation quality than employing just one machine translation service.
AB - An increased number of machine translation services are now available. Unfortunately, none of them can provide adequate translation quality for all input sources. This forces the user to select from among the services according to his needs. However, it is tedious and time consuming to perform this manual selection. Our solution, proposed here, is an automatic mechanism that can select the most appropriate machine translation service. Although evaluation methods are available, such as BLEU, NIST, WER, etc., their evaluation results are not unanimous regardless of the translation sources. We proposed a two-phase architecture for selecting translation services. The first phase uses a data-driven classification to allow the most appropriate evaluation method to be selected according to each translation source. The second phase selects the most appropriate machine translation result by the selected evaluation method. We describe the architecture, detail the algorithm, and construct a prototype. Tests show that the proposal yields better translation quality than employing just one machine translation service.
KW - Evaluation
KW - Machine Translation
KW - Service Selection
UR - http://www.scopus.com/inward/record.url?scp=85037109889&partnerID=8YFLogxK
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M3 - Conference contribution
AN - SCOPUS:85037109889
T3 - Proceedings of the 8th International Conference on Language Resources and Evaluation, LREC 2012
SP - 1771
EP - 1778
BT - Proceedings of the 8th International Conference on Language Resources and Evaluation, LREC 2012
A2 - Dogan, Mehmet Ugur
A2 - Mariani, Joseph
A2 - Moreno, Asuncion
A2 - Goggi, Sara
A2 - Choukri, Khalid
A2 - Calzolari, Nicoletta
A2 - Odijk, Jan
A2 - Declerck, Thierry
A2 - Maegaard, Bente
A2 - Piperidis, Stelios
A2 - Mazo, Helene
A2 - Hamon, Olivier
PB - European Language Resources Association (ELRA)
T2 - 8th International Conference on Language Resources and Evaluation, LREC 2012
Y2 - 21 May 2012 through 27 May 2012
ER -