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Mitigating the Effects of Delayed Virtual Agent Response Time Using Conversational Fillers

Virtual agents increasingly rely on cloud-based services, which makes them vulnerable to unpredictable network latency and service response times. In this work, we evaluate the use of conversational fillers to mitigate the impact of delay in system response time on users’ perception of a virtual agent. These fillers are uttered by the agent to keep the user engaged until the response is ready. We present the findings of a study run on the Mechanical Turk platform with 360 participants who interacted with a virtual agent. We tested two types of conversational fillers. The first type were generic utterances that simply asked the user to hold. The second adopted contextualized fillers that assume some semantic knowledge of the input and contain some of its elements. To test the generalizability of the different fillers, we ran two task-based experiments. The first task was to get a recipe and the second was to find a restaurant. Contextualized fillers positively affected participants’ rating of the agent’s response time but did not impact the agent’s likeability.