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Audiovisual prosody in problematic dialogue situations Marc Swerts Communication & Cognition Tilburg University.

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Presentation on theme: "Audiovisual prosody in problematic dialogue situations Marc Swerts Communication & Cognition Tilburg University."— Presentation transcript:

1 Audiovisual prosody in problematic dialogue situations Marc Swerts Communication & Cognition Tilburg 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): 1.Answers to factual questions (WISC, WAISC, Trivial Pursuit ). 2.Test how certain subject is (s)he would recognize the correct answer in a multiple- choice test (Feeling of Knowing (FOK)-scores). 3.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 Subjects and questions 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?...




13 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]

14 Eyebrow raising

15 Smile

16 Gaze (diverted)

17 Funny face

18 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 FOK correlationAnswersNon-answers Words-.344.401 Gaze acts-.309.347 Marked features-.422.462


20 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.

21 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?

22 Experiment 2: Perception of uncertainty (based on Brennan and Williams 1995) Stimuli: 60 adult responses from Experiment 1. AnswersNon-answers High FOK15 Low FOK15 120 subjects participated: Vision+soundSound onlyVision only 40 Task: judge level of uncertainty of speaker (FOAK scores).


24 FOAK scores for answers and nonanswers

25 Different conditions

26 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.

27 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. Child answersAdult-answers High FOK15 Low FOK15 Adult speakerChild speaker Adult judge20 Child judge20 80 subjects participated

28 adult judgeschild judges FOAK scores for children and adults

29 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.)

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

31 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

32 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%)


34 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

35 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? 2.User: Amsterdam System: So you want to travel to Rotterdam?

36 Users listening to system questions No problem Problem

37 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) 1.System: To which station do you want to travel? User: Rotterdam 2.System: So you want to travel to Amsterdam? User: Rotterdam

38 Slot filling (speakers utter destination) No ProblemProblem

39 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) 1.System: Do you want me to repeat the connection? User: No 2.System: So you want to travel to Amsterdam? User: No

40 Negations No ProblemProblem

41 Increasing level of frustration…

42 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

43 Degree of hyperarticulation Perceived problems Actual problems

44 Amount of visual variation Perceived problems Actual problems

45 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

46 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: Other interests: audiovisual cues to end-of-utterance, focus, emotion, deceptive speech, and personality; incorporation of findings in ECAs through collaborations

47 Data collection nFOK Correct answers5750.94 Incorrect answers1290.76 Non-answers960.42 nFOK Correct answers3710.96 Incorrect answers1250.74 Non-answers1310.50 Adults Children Contrary to adults, children have few high FOK non-answers.

48 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

49 Face:sure Face:unsure Voice:sureVoice:unsure

50 Face:sure Face:unsure Voice:unsureVoice:sure

51 Conclusions experiment 4 Overall: bias towards uncertainty in FOK ratings FOK ratings are significantly influenced by verbal (intonation pattern) and visual cues from the face; some speaker effect However, facial information has much stronger cue value


53 Series of studies Production of uncertainty (based on Smith and Clark 1993): “Feeling of Knowing” (FOK) –Experiment 1: Adults + children Perception of uncertainty (based on Brennan and Williams 1995): “Feeling of Another’s Knowing” (FOAK) –Experiment 2: Unimodal vs multimodal –Experiment 3: Adults x children

54 Future goals Integrate the findings in Embodied Conversational Agents in order to make these more natural and believable, in particular for error handling strategies (working hypothesis: Users are more likely to tolerate incorrect answers if the system signals its uncertainty) Explore whether visual features can be used as an additional resource for error detection (growing interest in incorporating visual information in automatic recognition process)

55 Audiovisual prosody Prosody defined as those features that do not determine what a speaker says, but rather how he or she says it –Verbal: intonation, tempo, loudness, voice quality, pauses, …. –Visual: facial expressions, hand and arm gestures, body language, … Audiovisual prosody = verbal + visual prosody

56 Self-presentation Auditory cues (Smith and Clark, 1993; Brennan and Williams, 1995): –Linguistic hedges (“I am not sure, but…”, “I think..”) –Filled pauses (uh and uhm) –Prosody (question intonation) This study: possible visual cues (are natural and important ingredient of daily conversations as well)

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