Japanese Chinese

Research on Japanese-Chinese translation focuses on improving the accuracy and efficiency of machine translation (MT) systems, particularly addressing challenges posed by complex linguistic structures like attributive clauses. Current efforts leverage large parallel corpora, often created through crowdsourcing and web mining techniques, and employ transformer-based neural machine translation (NMT) models, with optimizations like data sorting to enhance training speed. These advancements aim to improve the quality of automated Japanese-Chinese translation, impacting fields ranging from cross-cultural communication to language technology development.