The present contribution investigates the construction of

dialogue structure for the use in human-machine interaction

especially for robotic systems and embodied conversational

agents. We are going to present a methodology and findings of a

pilot study for the design of task-specific dialogues.

Specifically, we investigated effects of dialogue complexity on

two levels: First, we examined the perception of the embodied

conversational agent, and second, we studied participants’

performance following HRI. To do so, we manipulated the agent’s

friendliness during a brief conversation with the user in a

receptionist scenario.

The paper presents an overview of the dialogue system, the

process of dialogue construction, and initial evidence from an

evaluation study with naïve users (N = 40). These users

interacted with the system in a task-based dialogue in which they

had to ask for the way in a building unknown to them. Afterwards

participants filled in a questionnaire. Our findings show that

the users prefer the friendly version of the dialogue which

scored higher values both in terms of data collected via a

questionnaire and in terms of data collected during the run of

the experiment.

Implications of the present research for follow-up studies are

discussed, specifically focusing on the effects that dialogue

features have on agent perception and on the user’s evaluation

and performance.