Designing conversational agents: effect of conversational form on our comprehension

Abstract

We have developed a broadcasting agent system, public opinion channel (POC) caster, which generates understandable conversational form from text-based documents. The POC caster circulates the opinions of community members by using conversational form in a broadcasting system on the Internet. We evaluated its transformation rules in two experiments. In experiment 1, we examined our transformation rules for conversational form in relation to sentence length. Twenty-four participants listened to two types of sentence (long sentences and short sentences) with conversational form or with single speech. In experiment 2, we investigated the relationship between conversational form and the user’s knowledge level. Forty-two participants (21 with a high knowledge level and 21 with a low knowledge level) were selected for a knowledge task and listened to two kinds of sentence (sentences about a well-known topic or sentences about an unfamiliar topic). Our results indicate that the conversational form aided comprehension, especially for long sentences and when users had little knowledge about the topic. We explore possible explanations and implications of these results with regard to human cognition and text comprehension.