Doctoral Dissertation Research: Discourse relation annotation in speech databases

当说话者参与谈话时，他们会说出与他们和其他人所说的有意义的话语，这使得谈话或话语连贯。例如，发言者可能会详细阐述他们刚刚说的话，提供解释，或通过叙述连接多个事件。这些联系形成了所谓的话语之间的修辞或话语关系，并已使用多种理论和框架进行了研究。每一个人都提出了自己的一套名称为这些关系和分类的方法，但还没有一项研究，调查哪些类别的人实际上认为。对于人类和计算系统来说，识别这些关系也非常困难。在这个博士论文项目中，研究人员调查有多少和什么关系的英语发言人认为没有预设任何列表的话语关系。沿着博士生的培训，该项目收集的数据将提高我们对说话者如何感知和分类话语关系的理解，这些数据可用于改进对话代理和写作助手等计算系统。本项目从语义范畴化的角度研究语篇关系，即根据英语使用者感知的相似性来推断语篇关系的范畴。研究人员通过对自发对话数据的注释来测试这些类别。本论文项目包括两项研究-一个分类任务，其中包括一个分析的sperically-derived类的话语关系和现有的分类法，和语音数据库研究的基础上的一个子集的总机语音数据库的电话交谈的话语关系的注释。总之，该项目基于实证研究开发了适合口语会话数据的话语关系分类法，将英语使用者如何概念化话语关系与现有的话语关系分类法进行了比较，并建立了自发会话中话语关系的数据集，分析了说话者之间的差异和个体差异，该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

When speakers engage in conversation, they produce utterances that are meaningfully connected to what they and others have said, which makes the conversation or discourse coherent. For example, speakers may elaborate on what they just said, provide an explanation, or connect multiple events through narration. These connections form what are known as rhetorical or discourse relations between utterances and have been studied using multiple theories and frameworks. Each one has proposed its own set of names for these relations and ways of classifying them, but there has not yet been a study that investigates which categories people actually perceive. It is also very hard to identify these relations, both for humans and computational systems. In this doctoral dissertation project, researchers investigate how many and what relations English speakers perceive without presupposing any list of discourse relations. Along with training of a doctoral student, this project collects data that will improve our understanding of how speakers perceive and categorize discourse relations, which can be used to improve computational systems such as dialogue agents and writing assistants. This project approaches the study of discourse relations from a semantic categorization perspective, whereby categories of discourse relations are inferred based on similarity perceived by English speakers. The investigators test these categories through the annotation of spontaneous conversational data. The dissertation project consists of two studies – a categorization task, which includes an analysis of empirically-derived categories of discourse relations and existing taxonomies, and a speech database study based on the annotation of discourse relations on a subset of the Switchboard speech database of telephone conversations. Together, this project develops a taxonomy of discourse relations suitable for spoken conversational data based on empirical research, compares how discourse relations are conceptualized by English speakers to existing taxonomies of discourse relations, and builds a dataset of discourse relations in spontaneous conversations that analyzes variation and individual differences among speakers, and that can also be used as input or training data to computational systems or other applications.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.