La traduction multilingue : analyse d'une prouesse technologique

Abstract

Neural machine translation (NMT) systems have made tangible progress in recent years, making them usable for an increasing number of domains and language pairs. The development of neural systems is based on machine learning algorithms and requires large electronic corpora of parallel texts, aligned at the sentence level. Such resources however only exist for a small number of language pairs and domains. To overcome this problem, a recent proposal is to develop so-called “multilingual” translation systems. These developments have been driven in particular by major Internet players, who need to develop automatic language processing tools for as many languages as possible. The main characteristic of these systems is to process multiple languages, both on the source and target sides, with a single translation engine. In this paper, we present the general principles underlying these systems and the innovations that have made them possible, before discussing their main strengths and weaknesses.

Keywords

• neural machine translation
• multilingual machine translation
• cross-lingual transfer
• neural interlingua