A Review of Machine Translation Quality Assessment Methods

Abstract

Machine translation quality assessment plays a crucial role in enhancing the performance of machine translation systems. This review aims to survey and outline the current major methods used for assessing machine translation quality, which can be broadly categorized into manual and automatic assessment methods. Upon analyzing the existing literature, it becomes evident that while manual evaluation methods yield high-quality results, they are time-consuming and labor-intensive. On the other hand, automatic evaluation methods are cost-effective and rapid, but their evaluation results do not match the expertise of human evaluators. The objective of this paper is to furnish researchers with a comprehensive overview of machine translation quality assessment methods, enabling them to select appropriate approaches based on their specific experimental requirements. Additionally, we aspire to offer valuable insights and novel perspectives for further advancements in the field of machine translation quality assessment methods.