Computing Emotions
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As computer systems become more intelligent the interaction between users and systems, human-computer interaction (HCI), becomes less a matter of direct instructional control, and more a dialogue between two, not quite equal, parties. Creating believable, effective and engaging dialogues between users and systems requires that systems possess a wide range of capabilities beyond what is common today – for example speech recognition, gesture recognition, plan recognition and reference resolution. Emotions are also an important constituent in this mix as human computer interaction can often be quite emotionally charged. There are two main dimensions to the integration of emotion into human-computer interaction: emotion recognition and emotion simulation.
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Computing Emotions
- 1. Computing Emotions Brian Mac Namee John Kelleher Sarah Jane Delany School of Computing Dublin Institute of Technology Applied Intelligence Research Center
- 2. 1 2 Quantitative Recognising Models of Emotion Emotions Simulating Interesting Emotions Questions 3 4
- 3. QUANTITATIVE MODELS OF EMOTION
- 4. Lang Model Arousal alarmed astonished angry delighted annoyed frustrated glad happy Valence sad content satisfied bored calm
- 6. Ortony, Clore& Collins (OCC)
- 7. Ortony, Clore& Collins (OCC)
- 8. Ortony, Clore& Collins (OCC)
- 10. Emotion Recognition Emotion recognition has a wide range of uses: – Call centre monitoring – Automated tutors – Music retrieval – Market research – Online sentiment analysis – Law enforcement
- 11. Machine Learning Algorithm Training Examples Prediction Model
- 12. Machine Learning Algorithm Training Examples Prediction Model Disgust Happy Sad Angry
- 13. Machine Learning Algorithm Training Examples Prediction Model Positive Negative
- 14. Machine Learning Algorithm Training Examples Fear Prediction Model Anger Disgust Surprise Sadness Happiness
- 16. Feature Feature Feature Feature Feature ID 1 2 3 4 5 100 3.6 85 34 22 74
- 17. Feature Feature Feature Feature Feature ID 1 2 3 4 5 100 3.6 85 34 22 74 Prediction Model
- 18. Feature Feature Feature Feature Feature ID 1 2 3 4 5 100 3.6 85 34 22 74 Prediction Model Happiness
- 19. Emotion Recognition Examples Facial Emotion Recognition http://www.youtube.com/watch?v=45eLpzk6N34 Sentiment Analysis http://www.semantic-api.com/demo-statistical-sentiment-analysis.html
- 21. Emotion Simulation Emotion simulation is required in applications in which we need to simulate emotions: – Robotics – Automated speech systems – Games/entertainment systems There are two key parts to emotion simulation: – A model of emotion generation – A system for emotion realization
- 22. Lang Model Arousal Hand-crafted rules Insult about how particular Compliment actions lead to changes on the dimensions Valence within the model Very application specific
- 23. The OCC Model The OCC model has a sophisticated logical formalism for the generation of emotions Fear equals hope plus anticipated possible failure Failure after hope leads to disappointment
- 26. Emotion Generation Examples Kismet etc: http://www.youtube.com/watch?v=FE0zyCkhcbg http://web.media.mit.edu/~cynthiab/index.html
- 27. Emotion Generation Examples Façade: www.interactivestory.net http://www.youtube.com/watch?v=GmuLV9eMTkg
- 29. Interesting Questions What emotions are worth recognising and simulating and when? Are there models of human-human interaction from which lessons about the usefulness of emotion can be learned? What are the impacts of better emotional recognition and simulation for long term human robot interactions? Does it matter that the whole thing is a charade? What happens when users see behind the curtain?
- 30. Thank You Brian Mac Namee John Kelleher Sarah Jane Delany School of Computing Dublin Institute of Technology Applied Intelligence Research Center