The Influence of Context on Dialog Act Recognition
Table 4: Label distribution in the Switchboard Dialog Act Corpus (Replicated from [Jurafsky, Shriberg, and Biasca1997]).
['Label Statement-non-opinion', 'Count 72824', '% 36', 'Label Collab Completion', 'Count 699', '% .4']
The SWBD-DAMSL tag set was structured so that the annotators were able to label the conversations from transcriptions alone. It contains over 200 unique tag combinations. However, in order to obtain higher inter-annotator agreement and higher example frequencies per class, a less fine-grained set of 44 tags was devised. By analyzing the data, we came to the conclusion that merging segments labeled as Segment with the previous segment by the same speaker is the best approach, because some of the attributed labels only made sense when the segments were merged. Also, it makes sense to merge the Abandoned and Uninterpretable categories, because both represent disruptions in the dialog flow, which interfere with the typical dialog act sequence. However, in our experiments, we used the three variants of the tag set to allow direct comparison with the related work.