Students across the world in STEM classes, especially in the Global South, fall behind their peers who are more fluent in English, despite being at par with them in terms of scientific prerequisites. While many of them are able to follow everyday English at ease, key terms in English stay challenging. In most cases, such students have had most of their course prerequisites in a lower resource language. Live speech translation to lower resource languages is a promising area of research, however, models for speech translation can be too expensive on a large scale and often struggle with technical content. In this paper, we describe CueBuddy, which aims to remediate these issues by providing real-time "lexical cues" through technical keyword spotting along real-time multilingual glossary lookup to help students stay up to speed with complex English jargon without disrupting their concentration on the lecture. We also describe the limitations and future extensions of our approach.

翻译：全球范围内的STEM课堂学生，尤其是在全球南方地区，尽管在科学先修知识方面与同龄人相当，却往往落后于英语更流利的同学。虽然他们大多能轻松理解日常英语，但英语中的关键术语仍是挑战。在多数情况下，这类学生的课程先修知识主要通过资源较少的语言获得。面向低资源语言的实时语音翻译是一个前景广阔的研究领域，然而，大规模部署语音翻译模型成本高昂，且常难以处理技术性内容。本文介绍CueBuddy，该系统旨在通过实时技术关键词检测结合多语言术语表查询，提供实时"词汇提示"，帮助学生在不打断课堂听讲专注度的前提下，跟上复杂英语专业术语的节奏。文中亦探讨了该方法的局限性与未来扩展方向。