Robustness of a Spoken Dialogue Interface for a Personal Assistant

Although speech recognition systems have become more reliable in recent years, they are still highly error-prone. Other components of a spoken language dialogue system must then be robust enough to handle these errors effectively, to avoid recognition errors from adversely affecting the overall performance of the system. In this paper, we present the results of a study focusing on the robustness of our agent-based dialogue management approach. We found that while the speech recognition software produced serious errors, the dialogue manager was generally able to respond reasonably to users´ utterances.