數位工具於口譯詞彙表建立與口譯教學應用之初探

This study aims to explore the possibility of using automatic term extraction technologies to assist interpreting trainees acquire domain-specific terminology more efficiently. A small monolingual corpus based on speeches collected from online investment seminars was first built and a few commonly used term extraction tools were applied to extract finance-and-investment-related terms. The same speeches were also made available to a select group of interpreting trainees, who were required to produce glossaries as part of their pre-class preparations. The term extraction results and the manually-prepared glossaries were compared to determine how digital technologies may be best utilized to meet aspiring interpreters' needs. The comparison showed that there is still some gap between the kind of glossary deemed useful by the interpreter and the list of automatically extracted terms. (Semi)-Supervised models may prove more helpful to produce the desired glossary. Interpreting educators may consider using such term extraction technologies in preparation for their classes that focus on specialized domains.