Summary of the paper
| Title | Crowdsourcing for Evaluating Machine Translation Quality |
|---|---|
| Authors | Shinsuke Goto, Donghui Lin and Toru Ishida |
| Abstract | The recent popularity of machine translation has increased the demand for the evaluation of translations. However, the traditional evaluation approach, manual checking by a bilingual professional, is too expensive and too slow. In this study, we confirm the feasibility of crowdsourcing by analyzing the accuracy of crowdsourcing translation evaluations. We compare crowdsourcing scores to professional scores with regard to three metrics: translation-score, sentence-score, and system-score. A Chinese to English translation evaluation task was designed using around the NTCIR-9 PATENT parallel corpus with the goal being 5-range evaluations of adequacy and fluency. The experiment shows that the average score of crowdsource workers well matches professional evaluation results. The system-score comparison strongly indicates that crowdsourcing can be used to find the best translation system given the input of 10 source sentence. |
| Topics | Evaluation Methodologies, Machine Translation, SpeechToSpeech Translation |
Full paper  |
Crowdsourcing for Evaluating Machine Translation Quality |
| Bibtex | @InProceedings{GOTO14.756, author = {Shinsuke Goto and Donghui Lin and Toru Ishida}, title = {Crowdsourcing for Evaluating Machine Translation Quality}, 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} } |