Integrating Artificial and Human Intelligence for Efficient Translation
This work tackles the problem of optimizing translation workflows for translators and users, but it is incremental as it builds on existing post-editing practices.
The paper addresses the integration of artificial and human intelligence to enhance translation efficiency by shifting translators to post-editing machine-translated text, which saves time and improves quality, though no specific numbers are provided.
Current advances in machine translation increase the need for translators to switch from traditional translation to post-editing of machine-translated text, a process that saves time and improves quality. Human and artificial intelligence need to be integrated in an efficient way to leverage the advantages of both for the translation task. This paper outlines approaches at this boundary of AI and HCI and discusses open research questions to further advance the field.