Name
Abstract | ||
|---|---|---|
Interruptions are integral elements of natural spontaneous human interaction. Both competitive and cooperative interruption serve a distinct role in the flow of conversation. This paper analyzes their differences with features, change and activeness, employing audio, visual, and disfluency data. These features are able to capture differences between the two types of interruptions better than average feature values of any single modality. Also, discriminant analysis shows that the use of multimodal cues provides a 21% improvement in classification accuracy between the two types of interruptions relative to the baseline while any individual single modality cue does not provide significant improvement. |
Year | Venue | Keywords |
|---|---|---|
2008 | INTERSPEECH 2008: 9TH ANNUAL CONFERENCE OF THE INTERNATIONAL SPEECH COMMUNICATION ASSOCIATION 2008, VOLS 1-5 | human interaction,discriminant analysis |
Field | DocType | Citations |
Conversation,Pattern recognition,Computer science,Speech recognition,Human interaction,Artificial intelligence,Linear discriminant analysis | Conference | 10 |
PageRank | References | Authors |
1.01 | 8 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Chi-Chun Lee | 1 | 654 | 49.41 |
| Sungbok Lee | 2 | 1394 | 84.13 |
| Narayanan Shrikanth | 3 | 5558 | 439.23 |