论文标题
某些语言比其他语言更相等：深入探讨NLP世界中语言差异
Some Languages are More Equal than Others: Probing Deeper into the Linguistic Disparity in the NLP World
论文作者
论文摘要
NLP世界中的语言差异是最近被广泛认可的问题。但是，在NLP社区中很少讨论此问题的不同方面或这种差异背后的原因。本文对世界语言中存在的差异进行了全面分析。我们表明，仅考虑数据可用性的语言进行分类可能并不总是正确的。使用基于说话者人群和活力的现有语言分类，我们分析了语言数据资源的分布，NLP/CL研究的数量，包含在多语言Web的平台中，以及纳入预训练的多语言模型。我们表明，许多语言都没有在这些资源或平台中涵盖，甚至在属于同一语言群体的语言中，也存在很大差异。我们分析了家庭，地理位置，GDP和语言人群的影响，并为这种差异提供了可能的原因，以及一些建议以克服同样的建议。
Linguistic disparity in the NLP world is a problem that has been widely acknowledged recently. However, different facets of this problem, or the reasons behind this disparity are seldom discussed within the NLP community. This paper provides a comprehensive analysis of the disparity that exists within the languages of the world. We show that simply categorising languages considering data availability may not be always correct. Using an existing language categorisation based on speaker population and vitality, we analyse the distribution of language data resources, amount of NLP/CL research, inclusion in multilingual web-based platforms and the inclusion in pre-trained multilingual models. We show that many languages do not get covered in these resources or platforms, and even within the languages belonging to the same language group, there is wide disparity. We analyse the impact of family, geographical location, GDP and the speaker population of languages and provide possible reasons for this disparity, along with some suggestions to overcome the same.
