Affect Detection from Text-Based Virtual Improvisation and Emotional Gesture Recognition
We have developed an intelligent agent to engage with users in virtual drama improvisation previously. The intelligent agent was able to perform sentence-level affect detection from user inputs with strong emotional indicators. However, we noticed that many inputs with weak or no affect indicators a...
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| Format: | Article |
| Language: | English |
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Wiley
2012-01-01
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| Series: | Advances in Human-Computer Interaction |
| Online Access: | http://dx.doi.org/10.1155/2012/461247 |
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| _version_ | 1832567554060582912 |
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| author | Li Zhang Bryan Yap |
| author_facet | Li Zhang Bryan Yap |
| author_sort | Li Zhang |
| collection | DOAJ |
| description | We have developed an intelligent agent to engage with users in virtual drama improvisation previously. The intelligent agent was able to perform sentence-level affect detection from user inputs with strong emotional indicators. However, we noticed that many inputs with weak or no affect indicators also contain emotional implication but were regarded as neutral expressions by the previous interpretation. In this paper, we employ latent semantic analysis to perform topic theme detection and identify target audiences for such inputs. We also discuss how such semantic interpretation of the dialog contexts is used to interpret affect more appropriately during virtual improvisation. Also, in order to build a reliable affect analyser, it is important to detect and combine weak affect indicators from other channels such as body language. Such emotional body language detection also provides a nonintrusive channel to detect users’ experience without interfering with the primary task. Thus, we also make initial exploration on affect detection from several universally accepted emotional gestures. |
| format | Article |
| id | doaj-art-e2dc64cfc32d4cceac1c1d9e9f239d80 |
| institution | Kabale University |
| issn | 1687-5893 1687-5907 |
| language | English |
| publishDate | 2012-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Advances in Human-Computer Interaction |
| spelling | doaj-art-e2dc64cfc32d4cceac1c1d9e9f239d802025-02-03T01:01:15ZengWileyAdvances in Human-Computer Interaction1687-58931687-59072012-01-01201210.1155/2012/461247461247Affect Detection from Text-Based Virtual Improvisation and Emotional Gesture RecognitionLi Zhang0Bryan Yap1School of Computing, Engineering & Information Sciences, Northumbria University, Newcastle NE1 8ST, UKDepartment of Mechanical Engineering, University of Bristol, Bristol BS8 1TR, UKWe have developed an intelligent agent to engage with users in virtual drama improvisation previously. The intelligent agent was able to perform sentence-level affect detection from user inputs with strong emotional indicators. However, we noticed that many inputs with weak or no affect indicators also contain emotional implication but were regarded as neutral expressions by the previous interpretation. In this paper, we employ latent semantic analysis to perform topic theme detection and identify target audiences for such inputs. We also discuss how such semantic interpretation of the dialog contexts is used to interpret affect more appropriately during virtual improvisation. Also, in order to build a reliable affect analyser, it is important to detect and combine weak affect indicators from other channels such as body language. Such emotional body language detection also provides a nonintrusive channel to detect users’ experience without interfering with the primary task. Thus, we also make initial exploration on affect detection from several universally accepted emotional gestures.http://dx.doi.org/10.1155/2012/461247 |
| spellingShingle | Li Zhang Bryan Yap Affect Detection from Text-Based Virtual Improvisation and Emotional Gesture Recognition Advances in Human-Computer Interaction |
| title | Affect Detection from Text-Based Virtual Improvisation and Emotional Gesture Recognition |
| title_full | Affect Detection from Text-Based Virtual Improvisation and Emotional Gesture Recognition |
| title_fullStr | Affect Detection from Text-Based Virtual Improvisation and Emotional Gesture Recognition |
| title_full_unstemmed | Affect Detection from Text-Based Virtual Improvisation and Emotional Gesture Recognition |
| title_short | Affect Detection from Text-Based Virtual Improvisation and Emotional Gesture Recognition |
| title_sort | affect detection from text based virtual improvisation and emotional gesture recognition |
| url | http://dx.doi.org/10.1155/2012/461247 |
| work_keys_str_mv | AT lizhang affectdetectionfromtextbasedvirtualimprovisationandemotionalgesturerecognition AT bryanyap affectdetectionfromtextbasedvirtualimprovisationandemotionalgesturerecognition |