Proceedings Abstracts of the Twenty-Fifth International Joint Conference on Artificial Intelligence

Assessing Translation Ability through Vocabulary Ability Assessment / 3712
Yo Ehara, Yukino Baba, Masao Utiyama, Eiichiro Sumita

Translation ability is known as one of the most difficult language abilities to measure. A typical method of measuring translation ability involves asking translators to translate sentences and to request professional evaluators to grade the translations. It imposes a heavy burden on both translators and evaluators. In this paper, we propose a practical method for assessing translation ability. Our key idea is to incorporate translators' vocabulary knowledge for translation ability assessment. Our method involves just asking translators to tell if they know given words. Using this vocabulary information, we build a probabilistic model to estimate the translators' vocabulary and translation abilities simultaneously. We evaluated our method in a realistic crowdsourcing translation setting in which there is a great need to measure translators' translation ability to select good translators. The results of our experiments show that the proposed method accurately estimates translation ability and selects translators who have sufficient skills in translating a given sentence. We also found that our method significantly reduces the cost of crowdsourcing translation.