Turn-taking and turn-yielding phenomena in dialogs receive increasing attention nowadays. A growing number of spoken dialog systems inspire application designers to humanize people’s interaction experience with computers. The knowledge of psychology in discourse structure could be helpful in this effort. In this paper the authors explore effectiveness of selected visual and vocal turn-yielding cues in dialog systems using synthesized speech and an avatar. The aim of this work is to detect the role of visual and vocal cues on dialog turn-change judgment using a conversational agent. The authors compare and study the cues in two experiments. Findings of those experiments suggest that the selected visual turn-yielding cues are more effective than the vocal cues in increasing correct judgment of dialog turn-change. Vocal cues in the experiment show quite poor results and the conclusion discusses possible explanations of that.
Using finite state machines for evaluating spoken dialog systems
