Improvements in Analogical Learning: Application to Translating Multi-Terms of the Medical Domain

Handling terminology is an important matter in a translation workflow. However, current Machine Translation (MT) systems do not yet propose anything proactive upon tools which assist in managing terminological databases. In this work, we investigate several enhancements to analogical learning and test our implementation on translating medical terms. We show that the analogical engine works equally well when translating from and into a morphologically rich language, or when dealing with language pairs written in different scripts. Combining it with a phrasebased statistical engine leads to significant improvements.

• Type: Conference
• Year: 2009
• Where: EACL
• Authors: François Yvon, Philippe Langlais, Pierre Zweigenbaum
• Keywords: Analogical Engine, Analogical Learning, Current Machine Translation, EACL 2009, Natural Language Processing