Kernel-based Evaluation of Machine Translation

Abstract

Machine Translation (MT) is a research area in Natural Language Processing (NLP) which deals with the translation of input text from one source language to a target language. In order to estimate accurately the quality of MT systems, evaluation methods are required, beside the costly manual evaluation approaches. This thesis presents automatic methods for both reference-free and reference-based MT evaluation, which are based on tree and sequence kernel functions.