  To facilitate effective translation modeling and translation studies, one of
the crucial questions to address is how to assess translation quality. From the
perspectives of accuracy, reliability, repeatability and cost, translation
quality assessment (TQA) itself is a rich and challenging task. In this work,
we present a high-level and concise survey of TQA methods, including both
manual judgement criteria and automated evaluation metrics, which we classify
into further detailed sub-categories. We hope that this work will be an asset
for both translation model researchers and quality assessment researchers. In
addition, we hope that it will enable practitioners to quickly develop a better
understanding of the conventional TQA field, and to find corresponding closely
relevant evaluation solutions for their own needs. This work may also serve
inspire further development of quality assessment and evaluation methodologies
for other natural language processing (NLP) tasks in addition to machine
translation (MT), such as automatic text summarization (ATS), natural language
understanding (NLU) and natural language generation (NLG).
