Topic switch models for dialogue management in virtual humans
This paper presents a novel data-driven Topic Switch Model based on a cognitive representation of a limited set of topics that are currently in-focus, which determines what utterances are chosen next. The transition model was statistically learned from a large set of transcribed dyadic interactions....
| Main Authors: | , , |
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| Format: | Conference or Workshop Item |
| Published: |
2016
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| Online Access: | https://eprints.nottingham.ac.uk/35622/ |
| _version_ | 1848795122667356160 |
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| author | Zhu, Wenjue Chowanda, Andry Valstar, Michel F. |
| author_facet | Zhu, Wenjue Chowanda, Andry Valstar, Michel F. |
| author_sort | Zhu, Wenjue |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | This paper presents a novel data-driven Topic Switch Model based on a cognitive representation of a limited set of topics that are currently in-focus, which determines what utterances are chosen next. The transition model was statistically learned from a large set of transcribed dyadic interactions. Results show that using our proposed model results in interactions that on average last 2.17 times longer compared to the same system without our model. |
| first_indexed | 2025-11-14T19:27:04Z |
| format | Conference or Workshop Item |
| id | nottingham-35622 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| last_indexed | 2025-11-14T19:27:04Z |
| publishDate | 2016 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-356222020-05-04T18:11:39Z https://eprints.nottingham.ac.uk/35622/ Topic switch models for dialogue management in virtual humans Zhu, Wenjue Chowanda, Andry Valstar, Michel F. This paper presents a novel data-driven Topic Switch Model based on a cognitive representation of a limited set of topics that are currently in-focus, which determines what utterances are chosen next. The transition model was statistically learned from a large set of transcribed dyadic interactions. Results show that using our proposed model results in interactions that on average last 2.17 times longer compared to the same system without our model. 2016-09-20 Conference or Workshop Item PeerReviewed Zhu, Wenjue, Chowanda, Andry and Valstar, Michel F. (2016) Topic switch models for dialogue management in virtual humans. In: 16th International Conference on Intelligent Virtual Agents (IVA 2016), 20-23 Sept, 2016, Los Angeles, California, USA. Social relationship Framework Game-agents Interactions http://www.springer.com/us/book/9783319476643 |
| spellingShingle | Social relationship Framework Game-agents Interactions Zhu, Wenjue Chowanda, Andry Valstar, Michel F. Topic switch models for dialogue management in virtual humans |
| title | Topic switch models for dialogue management in virtual humans |
| title_full | Topic switch models for dialogue management in virtual humans |
| title_fullStr | Topic switch models for dialogue management in virtual humans |
| title_full_unstemmed | Topic switch models for dialogue management in virtual humans |
| title_short | Topic switch models for dialogue management in virtual humans |
| title_sort | topic switch models for dialogue management in virtual humans |
| topic | Social relationship Framework Game-agents Interactions |
| url | https://eprints.nottingham.ac.uk/35622/ https://eprints.nottingham.ac.uk/35622/ |