Analyse Des Structures D’ambiguité Syntaxique Et Sémantique D’un Corpus De Traduction Assistée Par Ordinateur Et Du Facteur Humain

Abstract

Machine translation has become predominant with the advancement in technology the world over. This has led to several benefits to the human translator as many of them use these translation tools to aid them in their work. In spite of their usefulness, these translation machines have several shortcomings of which ambiguity attracts our attention in this work. This research work aims at analyzing the problem of syntactic and semantic ambiguity in computer-assisted translations. It also identifies the role human translators play in correcting these errors made by the machines. This work would be done through an analysis and comparison of a corpus made by a computer assisted translator and another one by a human translator so as to identify gaps of syntactic and semantic ambiguity in machine translation, which impede the correct transfer of meaning from the source language to the target language. Through observation of the machine translated corpus, and subsequent analysis of the same corpus, we made some findings that, political and judicial texts mostly have minimal ambiguous sentences due to several editing and proof reading done by experts while literary texts present a lot more ambiguous sentences because of the imaginary nature of literature. The study would highlight the implications of ambiguity and the role human translators play in revising translations made by these machines.