Document Translation

Document translation aims to accurately and efficiently convert text within complex documents, including layout and visual cues, from one language to another. Current research focuses on improving neural machine translation models by addressing challenges like inconsistent OCR output and handling diverse document structures, often using benchmark datasets to evaluate performance. This field is crucial for bridging language barriers in diverse applications, from scientific literature access to multilingual communication, and ongoing work emphasizes improving both translation quality and efficiency through techniques like post-editing tools and crowdsourced data collection.