Where Will Low-resource Languages Go in the Context of ChatGPT?
As the natural language processing technology continues to evolve and proliferate,the Matthew effect in the field of language processing becomes increasingly evident.This phenomenon is primarily characterized by mainstream languages receiving more resources and attention,while low-resource languages face issues such as information silos and the digital divide.Since the training data for ChatGPT mainly comes from mainstream languages,its performance in low-resource languages is subpar.This al-so limits the language processing capabilities and applications for low-resource languages,thereby further exacerbating the Matthew effect.Embracing ChatGPT can help low-resource languages better integrate into the information exchange of the digital era,pro-moting global linguistic and cultural diversity.By adopting group intelligence perception,we can jointly advance the progress of low-resource language processing technology and foster global linguistic and cultural diversity and exchange.At the same time,ChatGPT also needs to focus on the quality control of data and information,as well as its adaptability and scalability in low-re-source languages.ChatGPT can enhance the informatization and natural language processing capabilities of low-resource languages,but it is also necessary to recognize that ChatGPT may exacerbate the Matthew effect.Therefore,measures need to be taken to en-sure that the development of this technology does not undermine the status of low-resource languages,with the aim of protecting and promoting the development of language diversity.
ChatGPTlow-resource languagethe Matthew effectdominant language issues
万方数据
维普
