March 2005 Affectemic Analysis Lesley Axelrod Kate Hone Brunel University, West London, UK.

March 2005

Affectemic Analysis

Lesley Axelrod

Kate Hone

Brunel University, West London, UK

Lesley AxelrodMarch 2005

Affectemic Analysis

Overview of Presentation

• Context of work at Brunel• Definitions• Analysing behaviours• Illustrative example• Preliminary results and discussion• Next steps?


Affectemic Analysis

Motivation for Research

EPSRC grant

Commenced October 2002

Emotion recognition technology is currently being developed with the aim of improving the quality of human-computer interaction.

Research in this domain emphasises solving the technical difficulties involved, through the design of ever more complex recognition algorithms.


Affectemic Analysis

Experimental Design

• To what extent and how do people naturally express emotions with extant systems?

• And how will when they behave if believe they are interacting with an affective system?

Hypothesis : that users will express more emotion:– if system acts affectively– if they are told that system is affective


Affectemic Analysis

Application development


Affectemic Analysis

WOZ scenario – different viewsParticipant Researcher


Affectemic Analysis

Transana

Transana – open source software – analysis tool - was originally created by Chris Fassnacht. It is now developed and maintained by David K. Woods at the Wisconsin Center for Education Research, University of Wisconsin-Madison.


Affectemic Analysis

Definitions

• Emotion - spectrum of personality traits, mood , states etc• Picard - Mount Everest analogy

- affect = whole spectrum of inner experiences

- emotional expressions = what is revealed to others

• Norman - affect = underlying and unconscious

- emotion = rational conscious element• Multimodal and multipurpose nature of communication• Kendon’s continuum• Bavelas – debunking body language


Affectemic Analysis

Human Communication of EmotionsWe use all of our senses, including our ‘sixth sense’, our environment and time to recognise and communicate feelings.

Appearance Movement Touch and Smell

Voice Space Time


Affectemic Analysis


Affectemic Analysis

Development of method for coding affective behaviours

IPA – Uses phonemes – sounds identified from use– any language – not all sounds occur in any one– phonetic – broad transcription commonly

adequate– allophones – variations of sounds can be

transcribed if necessary (phonemic or phonological transcription)

International Affective Alphabet IAA– Uses affectemes – expressions identified from use

– any language – not all expressions occur in any one

– affectemic – broad transcription commonly adequate

– allaffects – variations of expressions can be transcribed if necessary (affectic or affectological transcription)


Affectemic Analysis

Transcript Key words (allopnones) Keyword families (allaffects)

Development

of

coding

scheme


Affectemic Analysis

Reliability - Inter-observer agreementDouble codingOnset and offset boundariesRatings of valence and intensity

Cohen's kappa - agreement levels range 0.29 to 1.0, mode of 1.0 mean of 0.78.

Percentage agreements - range 89% to 100% mode 100% mean of 97.24

Validity Retrospective walkthroughs


Affectemic Analysis

Summary

– Affectemes are concerned with a multimodal, multipurpose communication approach. The Affectemes approach does not assume to map to underlying emotions, nor to be linked to particular theoretical basis of emotions, but hopes to identify communicative episodes.

– Affectemes are units of meaning. Perceived messages can be rated for valence and intensity.

– Affectemes are composed of lower order elements – body movements, intonation patterns, facial expressions etc

– Particular affectemes might be relevant for particular applications or used in particular types of domains.


Affectemic Analysis

Examples of wide range of emotional expressions


Affectemic Analysis

Allaffects

Example of variations of an emotional display


Affectemic Analysis

Main findings

VARIABLE SCORING SIG IN ACTED AFFECTIVE CONDITION

believed Yes/no .003 More participants believed the system was affective

believed game adapted

Yes/no .005 More believed game adapted to them

rungs completed Count .007 More rungs of game completed

SAM valence Rating Scale .002 After playing game more reported themselves as feeling happier

VARIABLE SCORING SIG IN TOLD AFFECTIVE CONDITION

Blinkrate count .037 Participants blinked more

AIM negative score Test score .043 More likely to report themselves as generally being susceptible to negative affect

Self reported showed emotion

Yes / no .042 More likely to say they had showed their emotions


Affectemic Analysis

What next?More analysis of existing data• Describe affectemes in set terms? (like manner voice and place of

phonemes)• Establish which channels are more important for particular types of

message?• Analyse onsets and offset times?• Compare to other more detailed coding schemes?• Develop non verbal appraisal analysis framework?• Investigate floods of basic emotions? • Look for sequential patterns? Use Anvil? • More on method – reliability decay?

A follow up experiment• Using protocol of common behaviours identified from first experiment – this

time comparing groups untrained or trained to use set affecticons.

March 2005

Affectemic Analysis

Lesley AxelrodKate Hone

Thanks to EPSRC for grant GR/R81374/01

“It doesn’t do to leave a live dragon out of your calculations if you live near him” Tolkein - Lord of the Rings

“I think the answer is a set of ethical standards of responsible practitioners….. I think it's a collaboration between the technologists and society. I mean, they say war is too important to leave to the generals. I think technology is too important potentially to the technologists. I think it's got to

be a whole social discussion.”Ray Kurzweil

March 2005 Affectemic Analysis Lesley Axelrod Kate Hone Brunel University, West London, UK.

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