We present recent work in the area of Cross-Domain Dialogue Act tagging. Our experiments investigate the use of a simple dialogue act classifier based on purely intra-utterance features - principally involving word n-gram cue phrases. We apply automatically extracted cues from one corpus to a new annotated data set, to determine the portability and generality of the cues we learn. We show that our automatically acquired cues are general enough to serve as a cross-domain classification mechanism.
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