Mihai: This will be my practice talk for the paper I will present at INTERSPEECH/EUROSPEECH.
Title:
Interactions between Speech Recognition Problems and User Emotions
Abstract:
Understanding how speech recognition problems affect the interaction with the user is a topic of great interest for the spoken dialogue community. We examine the dependencies between speech recognition problems in adjacent turns. We also examine the dependencies between speech recognition problems and student emotions within a turn and in adjacent turns. We apply Chi Square (χ2) analysis to a corpus of speech-based computer tutoring dialogues to discover these dependencies. We find that rejections are followed by more rejections than expected if there was no dependency between rejections, and that misrecognitions are followed by more misrecognitions than expected. We also find a strong dependency between recognition problems in the previous turn and user emotion in the current turn: after a system rejection there are more emotional user turns than expected. Surprisingly, in our data, we find no relationship between user emotions and recognition problems within a turn nor between previous turn user emotions and current turn recognition problems.
Diane: This will be my practice talk for Sigdial
Title:
Using Bigrams to Identify Relationships Between Student Certainness States and Tutor Responses in a Spoken Dialogue Corpus
Abstract:
We use n-gram techniques to identify dependencies between student affective states of certainty and subsequent tutor dialogue acts, in an annotated corpus of human-human spoken tutoring dialogues. We first represent our dialogues as bigrams of annotated student and tutor turns. We next use chi square analysis to identify dependent bigrams. Our results show dependencies between many student states and subsequent tutor dialogue acts. We then analyze the dependent bigrams and suggest ways that our current computer tutor can be enhanced to adapt its dialogue act generation based on these dependencies