Empirical determination of thresholds for optimal dialogue act classification

We present recent experiments which build on our work in the area of Dialogue Act (da) tagging. Identifying the dialogue acts of utterances is recognised as an important step towards understanding the content and nature of what speakers say. We describe a simple dialogue act classifier based on purely intra-utterance features — principally word n-gram cue phrases. Such a classifier performs surprisingly well, rivalling scores obtained using far more sophisticated language modelling techniques for the corpus we address. The approach requires the use of thresholds effecting the selection of n-gram cues, which have previously been manually supplied. We here describe a method of automatically determining these thresholds to optimise classifier performance.