Disfluencies (i.e. interruptions in the regular flow of speech), are ubiquitous to spoken discourse. Fillers ("uh", "um") are disfluencies that occur the most frequently compared to other kinds of disfluencies. Yet, to the best of our knowledge, there isn't a resource that brings together the research perspectives influencing Spoken Language Understanding (SLU) on these speech events. This aim of this article is to survey a breadth of perspectives in a holistic way; i.e. from considering underlying (psycho)linguistic theory, to their annotation and consideration in Automatic Speech Recognition (ASR) and SLU systems, to lastly, their study from a generation standpoint. This article aims to present the perspectives in an approachable way to the SLU and Conversational AI community, and discuss moving forward, what we believe are the trends and challenges in each area.

翻译：不流畅现象（即正常语流的中断）在口语语篇中普遍存在。与其他类型的不流畅现象相比，填充词（如"uh"、"um"）是最频繁出现的。然而，据我们所知，目前尚缺乏一个能够整合影响口语语言理解（SLU）对这些语音事件进行研究的学术资源。本文旨在全面综述多维视角：从潜在（心理）语言学理论出发，涵盖其在自动语音识别（ASR）和SLU系统中的标注与处理，最终延伸至从生成角度的研究。本文旨在以易于理解的方式向SLU与对话式AI领域呈现这些视角，并就各领域的未来趋势与挑战展开探讨。