论文标题
迈向深层多层方言分析：非裔美国人英语的案例研究
Towards a Deep Multi-layered Dialectal Language Analysis: A Case Study of African-American English
论文作者
论文摘要
当前，自然语言处理（NLP）模型扩散了语言歧视，从而导致了由于偏见的结果而产生潜在有害的社会影响。例如，在训练非裔美国人英语（AAE）时，接受主流美国英语（MAE）培训的言论式标签者会产生不可解剖的结果，这是由于培训期间看不到的语言功能而导致的。在这项工作中，我们结合了一个人类的范式，以更好地了解AAE说话者的行为及其语言使用，并强调需要方言包容性，以便本地AAE AEA的人可以与NLP系统进行广泛的互动，同时减少剥夺权利的感觉。
Currently, natural language processing (NLP) models proliferate language discrimination leading to potentially harmful societal impacts as a result of biased outcomes. For example, part-of-speech taggers trained on Mainstream American English (MAE) produce non-interpretable results when applied to African American English (AAE) as a result of language features not seen during training. In this work, we incorporate a human-in-the-loop paradigm to gain a better understanding of AAE speakers' behavior and their language use, and highlight the need for dialectal language inclusivity so that native AAE speakers can extensively interact with NLP systems while reducing feelings of disenfranchisement.
