1. humaine wp6 workshop 10/03/2005 1 annotation of emotions in meetings in the AMI project Roeland Ordelman* & Dirk Heylen Human Media Interaction University of Twente The Netherlands

2. humaine wp6 workshop 10/03/2005 2 overview on the AMI project: ~100 hours of audio/video recordings of project meetings on annotating the emotional state of the participants in the meetings on emotion annotation in AMI on implementing the annotation tool in the NXT framework

3. humaine wp6 workshop 10/03/2005 3 AMI in brief European Integrated Project of the IST 6th FWP, initiated in January 2004 and involving 15 partners aims at advancing the state-of-the-art in important basic technologies such as human-human communication modeling, speech recognition, computer vision, multimedia indexing and retrieval produces tools for off-line and on-line browsing of multi-modal meeting data, including meeting structure analysis and summarizing functions makes recorded and annotated multimodal meeting data widely available for the European research community, thereby contributing to the research infrastructure in the field

4. humaine wp6 workshop 10/03/2005 4 on the AMI meetings scenario-based meetings –participants are asked to carry out a certain task and are provided with role-restricted information –design project, involve one particular task (remote control design) –~35 hours (48 meetings) real design project meetings on –real design projects –such as engineering student projects, brochure or poster design, etc. –~35 hours other real or scenario-based meetings –cover a wider variety of meeting types, topics, behaviours, etc. –~30 hours

5. humaine wp6 workshop 10/03/2005 5 smart meeting rooms at three different sites (TNO, Edinburgh, IDIAP) –video (side camera, close up) –audio (mic-array, lapel, headset, manikin) –whiteboard strokes –pen on the recording of the meetings

6. humaine wp6 workshop 10/03/2005 6 ami annotations many features of meeting interactions are annotated: –speech –gestures –dialogue acts –posture –emotion information is used for (at least) three purposes: –primary meta-data source for multi-featured browsing of the recorded meetings. –training recognition algorithms that eventually should be able to provide automatically generated meta-data. –evidence on the basis of which theoretical models of human multi party interaction can be developed.

7. humaine wp6 workshop 10/03/2005 7 properties of the data ~100 hours of meeting data emotion annotation of every single speaker in meeting: 4 x 100 hours ! only a very small proportion can be expected to show emotional states in any strong sense neutral state will cover much data

8. humaine wp6 workshop 10/03/2005 8 emotion annotation no general agreement on how to annotate or label emotional content in a natural database a number of emotion annotation or labeling schemes have been proposed in the literature given the gradations and subtlety of emotions occurring in natural data, the labeling of emotion using category labels is not straightforward

9. humaine wp6 workshop 10/03/2005 9 emotion annotation in AMI Given: 1.the amount of data to be annotated, and 2.the expected gradations and subtlety of emotions occurring in meeting data a dimensional labeling approach complemented by a categorical labeling scheme seemed most appropriate in the context of AMI the FeelTrace software developed at Queens University Belfast (Cowie et al.) is reported to produce good quality annotations within a reasonable amount of time

10. humaine wp6 workshop 10/03/2005 10 FeelTrace judge the emotional experience of the participants of the meetings on two dimensions: arousal and valence.

11. humaine wp6 workshop 10/03/2005 11 annotation with FeelTrace in AMI survey on meeting specific landmarks pilot annotations re-implementation of FeelTrace

12. humaine wp6 workshop 10/03/2005 12 landmarks survey (1) (main investigator: Vincent Wan, University of Sheffield) Method: –list of 243 terms describing emotions –participants (37) had to select twenty emotions that they most frequently perceived in their meetings –participants from various companies and with various job descriptions, including lecturers, researchers, managers, secretaries and students. –243 terms were clustered by meaning into groups. The most frequently chosen one or two labels were shortlisted from each group. Taking some labels from each group ensures that there is sufficent coverage of the emotion space.

13. humaine wp6 workshop 10/03/2005 13 landmarks survey (2) list of 26 `meeting domain specific’ emotional words: at ease, bored, joking, annoyed, nervous, satisfied, frustrated, amused, relaxed, interested, cheerful, uninterested, disappointed, agreeable, contemplative, encouraging, sceptical, friendly, attentive, confused, confident, decisive, impatient, concerned, serious, curious

14. humaine wp6 workshop 10/03/2005 14 landmarks survey (3) second survey to determine where each of the shortlisted labels should appear in FeelTrace emotional space: –first presented participants with the five labels: anger, irritation, sadness, happiness and contentment (presented so that participants unfamiliar with FeelTrace would get some minimal experience in its use). –emotional words were presented twice: the first to allow the participant to gain additional training and the second to collect data.

15. humaine wp6 workshop 10/03/2005 15 example results 1

16. humaine wp6 workshop 10/03/2005 16 example results 2

17. humaine wp6 workshop 10/03/2005 17 example results 3

18. humaine wp6 workshop 10/03/2005 18 resulting landmark distribution

19. humaine wp6 workshop 10/03/2005 19 annotation trials we have 15-20 annotators available coming weeks: first annotation trials what do we want to learn: –inter-annotator agreement –distribution of emotional states in meeting data (how much is neutral) –annotator experience with tool –effect of using/not using landmarks –validation of manual, annotation area, etc

20. humaine wp6 workshop 10/03/2005 20 trial annotation set-up set of 4 meetings, each of about 20 minutes, 4 speakers per meeting 10 minute segments (0-10,10-20) (opt.) `dummy’ pass with Feeltrace `offical’ pass with FeelTrace with and without landmarks no categorical labeling (yet)

21. humaine wp6 workshop 10/03/2005 21 implementation in NXT Belfast implementation of dimensional approach knows some limitations: –no cross-platform support –cannot easily be tailored to specific needs from different `stakeholders’ of annotations (e.g., additional categorical of labeling of longer segments is hard in current setup)

22. humaine wp6 workshop 10/03/2005 22 stakeholders of annotation corpus developer –defines the structure of corpus, maintains the data, takes care of a proper data/tool distribution (CVS, validation, time) corpus annotator –needs to know as little as possible about configuration, installation and version control issues, only the annotation process itself is of concern for the annotator data consumer –interested in the annotations for analysis and may want to configure in detail the annotation process (tool functionalities such as redo, fastforward, landmarks/no- landmarks, ect) tool developer –creates the tool that serves the needs of the other users, keeping technical issues in mind

23. humaine wp6 workshop 10/03/2005 23 NXT Nite XML toolkit defines a data storage format that can easily be shared across a multitude of annotation and analysis tools for the many different aspects of a multi-modal corpus. the NXT libraries provide many ready-made components that facilitate easy development of new tools. expertise readily available at University of Twente

24. humaine wp6 workshop 10/03/2005 24 draft list of requirements easy distribution of data (and tools) to and from the annotators (e.g., annotate certain segments of a file, CVS functionality, batch functionality) easy management of multiple annotators, possibly working on the same data (e.g., CVS functionality) validation functionality or possibilities to plug this into the process as many input formats as possible on as many platforms as possible customizable landmarks, dimensions (1D, 2D, 3D), shortcuts categorical labeling options within the tool video control (fastforward/backward) progress bar replay annotation aligned with video selection of multiple video signals (close up, wide angle) color coding of the 2D space (provide a priori color feedback instead of feedback with a changing color of the cursor) easy configuration in general → discuss requirements with AMI/HUMAINE researchers

25. humaine wp6 workshop 10/03/2005 25 roadmap starting first trial annotations investigate trial results discuss re-implementation of FeelTrace in NXT with interested parties and create an first implementation version follow-up trials, FeelTrace-NXT versions monitor process and discuss results with researchers in the field (AMI, Humaine)