Structured interviews are used in many settings, importantly in market research on topics such as brand perception, customer habits, or preferences, which are critical to product development, marketing, and e-commerce at large. Such interviews generally consist of a series of questions that are asked to a participant. These interviews are typically conducted by skilled interviewers, who interpret the responses from the participants and can adapt the interview accordingly. Using automated conversational agents to conduct such interviews would enable reaching a much larger and potentially more diverse group of participants than currently possible. However, the technical challenges involved in building such a conversational system are relatively unexplored. To learn more about these challenges, we convert a market research multiple-choice questionnaire to a conversational format and conduct a user study. We address the key task of conducting structured interviews, namely interpreting the participant's response, for example, by matching it to one or more predefined options. Our findings can be applied to improve response interpretation for the information elicitation phase of conversational recommender systems.

翻译：结构化采访广泛应用于多种场景，尤其在品牌认知、消费者习惯或偏好等市场研究主题中，这些研究对产品开发、市场营销及电子商务整体至关重要。此类采访通常由一系列问题构成，面向参与者提问。受访过程一般由经验丰富的采访者执行，他们能解读参与者的回应并据此灵活调整采访内容。若采用自动化对话代理实施此类采访，将有望覆盖比当前更广泛、更多样化的参与者群体。然而，构建此类对话系统所涉及的技术挑战尚未得到充分探索。为深入了解这些挑战，我们将一份市场研究中的选择题问卷转换为对话格式并开展用户研究。我们聚焦于进行结构化采访的核心任务，即解读参与者回应，例如将其匹配至一个或多个预设选项。相关发现可用于改进对话推荐系统中信息获取阶段的回应解读能力。