Multilingualism refers to the high degree of proficiency in two or more
languages in the written and oral communication modes. It often results in
language mixing, a.k.a. code-mixing, when a multilingual speaker switches
between multiple languages in a single utterance of a text or speech. This
paper discusses the current state of the NLP research, limitations, and
foreseeable pitfalls in addressing five real-world applications for social good
crisis management, healthcare, political campaigning, fake news, and hate
speech for multilingual societies. We also propose futuristic datasets, models,
and tools that can significantly advance the current research in multilingual
NLP applications for the societal good. As a representative example, we
consider English-Hindi code-mixing but draw similar inferences for other
language pairs

讨论多语社会中 NLP 研究的现状、局限与未来的发展。提出英汉混合语言作为案例，探究五个涉及到社会福祉的应用领域：危机管理、医疗保健、政治宣传、假新闻与仇恨言论等。同时，提出了未来多语言 NLP 应用中可能涉及到的数据集、模型和工具。