1 Evidence of Emotion Julia Hirschberg [email protected].

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1 Evidence of Emotion Julia Hirschberg [email protected]
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Transcript of 1 Evidence of Emotion Julia Hirschberg [email protected].

Page 1: 1 Evidence of Emotion Julia Hirschberg julia@cs.columbia.edu.

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Evidence of Emotion

Julia Hirschberg

[email protected]

Page 2: 1 Evidence of Emotion Julia Hirschberg julia@cs.columbia.edu.

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Agenda

• Class introductions• Paper discussion• Lessons learned:

– Formulating discussion questions

– Leading a discussion

• Future discussion leaders

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Controversies

• Do studies of emotion need a theoretical framework or should we just ‘get back to observable data’?

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Cornelius ’00: Theoretical Approaches to Emotion

• Claims: – Theories of emotion are essential to the study of

emotion

– They are actually implicit in work done by researcher who may not be aware of their own assumptions

• What is the nature of emotion?

• How should we study emotion?

• How can we explain emotion?

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Four Perspectives

• Darwinian: Natural selection– Function: Emotions evolve to help humans survive

– Same in everyone and similar in related species

• Similar display for Big 6+ (happiness, sadness, fear, disgust, anger, surprise) ‘basic’ emotions

• Similar understanding of emotion across cultures

• What is the evidence? Implications?

• Jamesian: Emotion is experience– Perception of bodily changes emotion

• ‘We are afraid because we run’ ?

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– Automatic responses to environment that help us survive

– Each emotion accompanied by unique pattern of bodily responses

– What is the evidence? Implications?

• Cognitive: Appraisal (e.g. Arnold’s “sense judgments”)– What is appraisal?– How does this relate to Darwin and James?– What is the evidence?– How has appraisal theory been criticized?– What consequences for studying emotion?– How identify appraisal components? E.g. happiness– Scherer’s (’87, ’99) stimulus/evaluation checks

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• Social Constructivism: Social Function/ Cultural Dependence– Emotions arise from learned social rules – what does

emotion X achieve in my culture? E.g. anger

– Gender and group differences

– Relationship with appraisal theory?

– Implications for study of emotion?

• Are these theories converging?• What differences remain?• Do we need to adopt a theory of emotion to study

emotion?

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Controversies

• Should the data we ‘observe’ be– From natural speech (corpora)

– Elicited in laboratories

• From actors?

• From non-professional subjects?

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happysadangryconfidentfrustratedfriendlyinterested

anxiousboredencouraging

Acted Speech: LDC Emotional Speech Corpus

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Is Natural Emotion Different? (thanks to Liz Shriberg)

• Neutral– July 30

– Yes

• Disappointed/tired– No

• Amused/surprised

– No

• Annoyed– Yes– Late morning

• Frustrated– Yes– No

– No, I am … – …no Manila...

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Wilting et al ’06: Real vs. acted emotional speech

• Research questions:– Do actors feel acted emotions?

– Ecological validity: Is acted emotional speech the same as ‘real’ emotional speech

• Terminology– Within subjects vs. between subjects: pros and cons

– Dependent and independent variables

– Conditions

– Debriefing

– T-test, ANOVA, Tukey HSD

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• Audiovisual Experiments– Hypothesis

– Experimental design

– Participants

– Results

– Conclusions

• Are these good experiments?• Do they have any weaknesses?• Would you have done anything differently?• What can we conclude from these experiments?

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Enos & Hirschberg ’06: A New Approach to Acted Emotional Speech

• What is the goal of this paper?• What theoretical assumptions does it make?

– Which of Cornelius theories does it assume, if any?

– Abelson ’83: Cognitive Consistency Theory

• What do the authors propose to do to collect more natural emotional speech?– Scenario approach

– Script approach

– Do you think either would work? What are the drawbacks?

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Nisimura et al ’06: Analyzing Dialogue Data for Real-World Emotional Speech Classification

• Goal: Classify child utterances wrt ‘delightful’ or ‘hateable’ emotions

• How did they obtain and annotate the data?• What was the method of analysis?

– Factor analysis

– Support vector machine

– Regression analysis

– Jackknife method

• What can we conclude from this experiment?

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Asking Good Questions

• Think about higher level issues the authors raise more than detail-oriented questions unless you find some details controversial or confusing– How does the paper relate to the general topic for this

week? What does it contribute?– What are the controversial claims?– Compare pros and cons of the approach – how could it

be improved?– Compare points of agreement and disagreement with

the other papers– Point out directions for future research– What are the implications for the field?

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Leading Discussions

• Provide a framework/context for the approach taken in the paper

• Highlight the main points and contributions• Point out claims or results you find controversial• Explain any technical points you think will be

difficult to understand• Discussion leader assignments

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Next Week

• Read: Johnstone et al ’06, look at the Ekman video and bio, look at the Wikipedia article on FACS

• Prepare discussion questions on each• Bring 2-3 ideas for your project to class