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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Yangyang Shi Wiggers, P. Jonker, C.M. |
| Copyright Year | 2011 |
| Description | Author affiliation: Man-Machine interaction group, Mediamatics department, EWI, Delft University of Technology, the Netherlands (Yangyang Shi; Wiggers, P.; Jonker, C.M.) |
| Abstract | We present a method for automatic classification of the socio-situational setting of a conversation based on the language used. The socio-situational setting depicts the social background of a conversation which involves the communicative goals, number of speakers, number of listeners and the relationship among the speakers and the listeners. Knowledge of the socio-situational setting can be used to search for content recorded in a particular setting or to select context-dependent models for example for speech recognition. We investigated the performance of different feature sets of conversation level features and word level features and their combinations on this task. Our final system, that classifies the conversations in the Spoken Dutch Corpus in one of 14 socio-situational settings, achieves an accuracy of 89.55%. |
| Starting Page | 455 |
| Ending Page | 460 |
| File Size | 145959 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781467303651 |
| e-ISBN | 9781467303675 |
| e-ISBN | 9781467303668 |
| DOI | 10.1109/ASRU.2011.6163974 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2011-12-11 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Speech Accuracy Feature extraction Vectors Training Kernel Context modeling |
| Content Type | Text |
| Resource Type | Article |
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