本文介紹了一種基于自然語言了解(NLU)的議論文對話系統架構。我們的方法可以區分多個使用者意圖，并識别使用者在其自然語言中引用的系統參數。我們的模型适用于一個議論性對話系統，該系統允許使用者告知自己關于一個有争議的話題并建立自己的觀點。為了評估所提出的方法，我們收集了使用者與各自系統互動的話語，并在一個廣泛的線上研究中标注意圖和參考論點。資料收集包括多個主題和兩種不同的使用者類型(來自英國的母語使用者和來自中國的非母語使用者)。評價表明所使用的技術比基線方法有明顯的優勢，以及針對新主題和不同的語言能力以及使用者的文化背景所提出的方法的穩健性。
原文标題：Natural Language Understanding for Argumentative Dialogue Systems in the Opinion Building Domain
原文：This paper introduces a natural language understanding (NLU) framework for argumentative dialogue systems in the information-seeking and opinion building domain. Our approach distinguishes multiple user intents and identifies system arguments the user refers to in his or her natural language utterances. Our model is applicable in an argumentative dialogue system that allows the user to inform him-/herself about and build his/her opinion towards a controversial topic. In order to evaluate the proposed approach, we collect user utterances for the interaction with the respective system and labeled with intent and reference argument in an extensive online study. The data collection includes multiple topics and two different user types (native speakers from the UK and non-native speakers from China). The evaluation indicates a clear advantage of the utilized techniques over baseline approaches, as well as a robustness of the proposed approach against new topics and different language proficiency as well as cultural background of the user.
Natural Language Understanding for Argumentative Dialogue Systems in the Opinion Building Domain.pdf