维吾尔语机器翻译研究综述OACSTPCD

As one of the important tasks in China's low-resource machine translation research,the development and application of Uyghur machine translation can better promote cultural exchanges and trade between different regions and ethnic groups.However,Uyghur,as an adhesive language,has problems such as complex morphology and a scarce corpus in the field of machine translation.In recent years,at different stages of the development of Uyghur machine translation,researchers have optimized and innovated algorithms and models to address its characteristics and achieved various research results;however,no systematic review has been conducted.The paper comprehensively reviews the related research on Uyghur machine translation and categorizes it into three types according to methods used:rule-and example-based Uyghur machine translation,statistics-based Uyghur machine translation,and neural network-based Uyghur machine translation.Related academic activities and corpus resources are also summarized.To further explore the potential of Uyghur machine translation,the ChatGPT model is adopted as a preliminary attempt of the Uyghur-Chinese machine translation task.The experimental results show that in the Few-shot scenario,the translation performance is higher and then decreases with an increase in the number of examples,and the best performance is for 10-shot.Also,the chain-of-thought approach does not demonstrate better translation ability in the Uyghur machine translation task.Finally,future research directions for Uyghur machine translation are proposed.