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General problem

Audiovisual prosody in problematic dialogue situations Marc Swerts Communication & Cognition Tilburg University. General problem. Spoken dialogue systems (SDS) are prone to error, especially because of errors in the ASR component of such systems

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General problem

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  1. Audiovisual prosody in problematic dialogue situationsMarc SwertsCommunication & CognitionTilburg University

  2. General problem • Spoken dialogue systems (SDS) are prone to error, especially because of errors in the ASR component of such systems • Errors will remain a problem for future systems, e.g. when they have to operate in noisy conditions, with non-native speakers or when the domain of the system becomes larger • Therefore: key task for most dialogue managers in SDS systems is error handling: • Prevent errors (e.g. optimal dialogue strategies) • Detect errors (e.g. acoustic and semantic confidence scores) • Correct errors (e.g. feedback cues, system prompts)

  3. Prosody and error handling • Recent interest in the use of speech prosody for error handling • To detect misrecognized utterances which have been shown to be prosodically different from correctly recognized utterances (e.g. Hirschberg et al. 2004) • To distinguish positive from negative feedback cues about the smoothness of the interaction (e.g. Krahmer et al. 2002) • To locate places where speakers try to correct a prior utterance (corrections tend to be hyperarticulated, which often leads to ‘spiral’ errors) (Oviatt et al. 1998) • Previous research only focused on verbal features; in this talk we concentrate on the effect of errors on visual features as well (audiovisual prosody)

  4. This talk • Report on analyses of interactions between speakers and their dialogue partners (both humans and machine) • Study audiovisual features of speakers • When speakers notice they themselves have a problem (Part 1) • When speakers notice their dialogue partners have a problem (Part 2)

  5. Part 1 • What are audiovisual features of a speaker who experiences communication problems?

  6. Uncertainty • Speakers are not always equally confident about or committed to what they are saying • Suppose someone asks a question (Who wrote hamlet? What is the capital of Switzerland?) • Speakers may be sure about their answer, or rather uncertain • Speakers may not know the answer, though it may be on the tip of their tongue • These differences in confidence level are reflected in the way speakers present themselves; this is useful for their addressees

  7. Questions to be addressed • How can visual cues from a speaker’s face be used as signals of level of uncertainty? How important are such cues compared to auditory cues? • Are their significant differences between different kinds of speakers in their use of visual cues for uncertainty? (here: age differences)

  8. Experiment 1: Production of Uncertainty(based on Smith and Clark 1993) • Experiment in three stages (Hart 1965): • Answers to factual questions (WISC, WAISC, Trivial Pursuit ). • Test how certain subject is (s)he would recognize the correct answer in a multiple-choice test (Feeling of Knowing (FOK)-scores). • Recognition test (Multiple-choice). • “Tip of the tongue”: non-answer (“I don’t know”) with a high FOK. • Subjects were filmed during first test; they could not see the experimentor. • Adults: person with highest score got a small reward. • Children all got a small award

  9. 20 adults Students and collegues [20 – 50] 40 questions n = 800 Who wrote Hamlet? How many degrees in a circle? What is the capital of Switzerland? ... 20 children Group 4 [7 – 8] 30 questions n = 600 Who is the president of the U.S.? Where can you buy a Happy Meal? What is the color of peanut butter? ... Subjects and questions

  10. Labelling • All 1400 utterances were manually labelled by 4 independent judges. • Consensus labeling of presence/absence of different audio-visual features. • Verbal: high intonation, filled pauses, delay, number of words. • Visual: eyebrow, smile, “funny face”, gaze [adults only]

  11. Eyebrow raising

  12. Smile

  13. Gaze (diverted)

  14. Funny face

  15. Results adults • Answers: Presence of filled pause, delay, high intonation, eyebrow, smile, funny face and different gaze acts correspond with significantly lower FOK score. • Non-answers: Presence of filled pause, delay, high intonation, eyebrow, smile, funny face and different gaze acts correspond with significantly higher FOK score

  16. Results children • Answers: Presence of eyebrow, funny face and delay correspond with significantly lower FOK score. • Non-answers: Presence of smile corresponds with a significantly higher FOK score. • Other than that no significant findings. • In general: children are much less expressive than adults, use occasionally very long delays, and hardly any filled pauses.

  17. Conclusion experiment 1 • Speakers express their level of uncertainty via various audiovisual cues. • Adults do this much more than children (‘self-presentation’) • Opposite findings for answers and nonanswers. • How is uncertainty perceived? What are the important features? • In different modalities? • By different judges?

  18. Experiment 2: Perception of uncertainty(based on Brennan and Williams 1995) • Stimuli: 60 adult responses from Experiment 1. 120 subjects participated: Task: judge level of uncertainty of speaker (FOAK scores).

  19. FOAK scores for answers and nonanswers

  20. Different conditions

  21. Conclusion experiment 2 • Observers can estimate a speaker’s level of uncertainty on the basis of audiovisual cues. • Answers are “easier” than nonanswers. • Scores for unimodal stimuli are good (both sound only and vision only), but those for bimodal stimuli go best.

  22. Experiment 3: Perception of uncertainty • For different speakers/judges: adults vs. children • Same task: judge level of (un)certainty • Stimuli: only answers, selected from experiment 1. 80 subjects participated

  23. FOAK scores for children and adults adult judges child judges

  24. Conclusion experiment 3 • Adults are “better” judges than children.(Detecting behavior one does not display is more difficult..) • Adults are “better” judged than children.(What is not signalled cannot be detected.)

  25. Part 2 • What are audiovisual features of a speaker who notices that his/her dialogue partner has communication problems?

  26. Feedback cues • Dialogue partners continuously send and receive signals on the status of the information which is being exhanged • Positive feedback cues (‘go on’) when there are no problems • Negative feedback cues (‘go back’) when there are problems • Previous research revealed that negative feedback cues are prosodically ‘marked’ (e.g. higher, louder, longer) (e.g. Krahmer et al. 2002, Shimojima et al. 2002) • Here: series of experiments to investigate whether speakers use visual cues as well as auditory ones for distinguishing positive from negative cues

  27. Data • Taken from an audiovisual corpus of 9 subjects engaged in telephone conversations with a speaker-independent traintime table information system; they had to query the system on 7 train journeys (63 interactions) • Subjects were video-taped during their interactions; they were led to believe the data collection for the development of a new video-phone • 76% of the dialogues were successfully completed; 374 out of 1183 speaker turns were misunderstood by the system (32%)

  28. Set-up of perception experiment • We performed three perception experiments in which 66 subjects were shown selected video-clips from these recorded human-machine interactions • The clips constituted ‘minimal pairs’, in that they consisted of comparable utterances that had originally occurred either in a problematic or in an unproblematic dialogue exchange • The subjects’ task was to guess whether the presented clip came from a problematic or unproblematic context

  29. Study 1: verification questions • Subjects saw users listening to verification questions from the system (so users are silent), which can be unproblematic (such as in 1), or problematic (such as in 2) 1. User: Amsterdam System: So you want to travel to Amsterdam? • User: Amsterdam System: So you want to travel to Rotterdam?

  30. Users listening to system questionsNo problem Problem

  31. Study 2: Destination utterances • Subjects saw speakers uttering a destination; this could the speaker’s first attempt (unproblematic) (like in 1), or it could be a correction in response to a verification question of misrecognized or misunderstood information (like in 2) • System: To which station do you want to travel? User: Rotterdam • System: So you want to travel to Amsterdam? User: Rotterdam

  32. Slot filling (speakers utter destination)No Problem Problem

  33. Study 3: negations • Subjects saw speakers uttering a negation (“nee”, no), which could be a response to a general yes-no question (like in 1), or a response to a verification question which contains incorrect information (like in 2) • System: Do you want me to repeat the connection? User: No • System: So you want to travel to Amsterdam? User: No

  34. NegationsNo Problem Problem

  35. Increasing level of frustration…

  36. Findings • In all three studies, subjects were able to correctly distinguish problematic from unproblematic fragments above chance level (task was easier for verification stimuli, and slot fillers) • In order to gain insight into the audiovisual features that may have functioned as cues we labeled the data in terms of level of hyperarticulation (6 levels), and presence or absence of a number of visual features (most important: smile, head movement, diverted gaze, frown, brow raise) • Both level of hyperarticulation and relative number of visual cues were correlated with perceived and actual problems

  37. Degree of hyperarticulation Perceived problems Actual problems

  38. Amount of visual variation Perceived problems Actual problems

  39. General conclusion • Dialogue problems have been shown to have consequences for audiovisual characteristics of a speaker who experiences problems him/herself or who notices that the dialogue partner has communication problems • In general, it appears that problematic dialogue situations lead to more dynamic facial expressions and marked prosodic behaviour

  40. More information • Research reported here joint work with Emiel Krahmer, Pashiera Barkhuysen (PhD project) and Lennard van de Laar (technical assistant) within the FOAP (“Functions of audiovisual prosody”) project: foap.uvt.nl • Other interests: audiovisual cues to end-of-utterance, focus, emotion, deceptive speech, and personality; incorporation of findings in ECAs through collaborations

  41. Data collection Adults Children Contrary to adults, children have few high FOK non-answers.

  42. Manipulated data • Gain more insight into relevance of visual and auditory cues; because of ceiling effects it was difficult to establish the strength relation between these two types of cues • Answers (1 HighFOK, 1 LowFOK) from 5 speakers were selected; words had to have a similar sound shape (e.g. Goethe-Goofy; Zurich-Zorro, …) • Sound and image were separated to create mixed stimuli (e.g. HighFOK vision combined with LowFOK sound) • Both original and mixed stimuli were presented to 120 subjects who had to rate the FOK level (7-point scale) of each stimulus

  43. Face:sure Face:unsureVoice:sure Voice:unsure

  44. Face:sure Face:unsureVoice:unsure Voice:sure

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