知識に基づく対話フロー管理：ソーシャルロボットと対話エージェント向け
Knowledge-Grounded Dialogue Flow Management for Social Robots and Conversational Agents
オントロジーを用いて会話トピックを知識ベースで管理し、ユーザーの意図に沿った自然な対話の流れを実現する対話管理アルゴリズムを提案。100名の参加者による5種類のエージェント比較実験で評価した。
著者: Lucrezia Grassi, Carmine Tommaso Recchiuto, Antonio Sgorbissa
分類: cs.RO, cs.HC
原文アブストラクト
The article proposes a system for knowledge-based conversation designed for Social Robots and other conversational agents. The proposed system relies on an Ontology for the description of all concepts that may be relevant conversation topics, as well as their mutual relationships. The article focuses on the algorithm for Dialogue Management that selects the most appropriate conversation topic depending on the user's input. Moreover, it discusses strategies to ensure a conversation flow that captures, as more coherently as possible, the user's intention to drive the conversation in specific directions while avoiding purely reactive responses to what the user says. To measure the quality of the conversation, the article reports the tests performed with 100 recruited participants, comparing five conversational agents: (i) an agent addressing dialogue flow management based only on the detection of keywords in the speech, (ii) an agent based both on the detection of keywords and the Content Classification feature of Google Cloud Natural Language, (iii) an agent that picks conversation topics randomly, (iv) a human pretending to be a chatbot, and (v) one of the most famous chatbots worldwide: Replika. The subjective perception of the participants is measured both with the SASSI (Subjective Assessment of Speech System Interfaces) tool, as well as with a custom survey for measuring the subjective perception of coherence.
