Corpus-Assisted Expansion of Manual MT Knowledge
Setsuo Yamada, Kenji Imamura, Kazuhide Yamamoto · 2002
Since the expansion of MT knowledge is currently being performed by humans, it is taking too long and is too expensive. This paper proposes a new procedure that expands MT knowledge e#ciently by supporting human judgements with information automatically collected from any number of corpora. The new procedure uses the source knowledge present in an MT system as the key to retrieve source language information from corpora. It also uses the partial translations provided by the MT to acquire target language information. These two techniques can reduce time and labor costs. Experimental results confirm both benefits.