Detecting emotional state of a child in a conversational computer game

Yıldırım, Serdar; Narayanan, Shrikanth; Potamianos, Alexandros

doi:10.1016/j.csl.2009.12.004

Cited by 81 publications

(43 citation statements)

References 33 publications

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“…In comparison to the values of neutral statements, there was a significant difference in the pitch of statements classified as cues and concerns by the VR-CoDES. The statistical difference, higher f0 averages, indicates a trend consistent with the literature that individuals use an increase in the pitch of their voice when speaking with anxiety or other emotional arousal [13][14][15][16][17][18][19]. It is difficult to assign a level that would be considered a clinical difference.…”

Section: Discussionsupporting

confidence: 51%

“…Reviewing the literature on vocal characteristics of human affect, fundamental frequency of pitch (f0), has been identified as one of the most reliable tools, essential for detecting emotional arousal using the voice [13][14][15][16][17][18][19]. However, no study has yet used this objective measure of emotional distress to characterise patient concern in the clinical oncology setting.…”

Section: Fundamental Frequency Of Pitch (F0)mentioning

confidence: 99%

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Using fundamental frequency of cancer survivors’ speech to investigate emotional distress in out-patient visits

Kandsberger

Rogers

Zhou

et al. 2016

Patient Education and Counseling

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2 Highlights  Emotions in clinical conversations of cancer patients studied by a coding system and speech prosody  Emotional energy f0 was associated with cues and concerns as coded by VR-CoDES system  An additional aid to study emotional speech with potential to reveal hidden content and meaning AbstractObjective: Emotions, are in part conveyed by varying levels of fundamental frequency of voice pitch (f0). This study tests the hypothesis that patients display heightened levels of emotional arousal (f0) during Verona Coding Definitions of Emotional Sequences (VR-CoDES) cues and concerns versus during neutral statements. Methods:The audio recordings of sixteen head and neck cancer survivors' follow-up consultations were coded for patients' emotional distress. Pitch (f0) of coded cues and concerns, including neutral statements was extracted. These were compared using a hierarchical linear model, nested for patient and pitch range, controlling for statement speech length. Utterance content was also explored. Results:Clustering by patient explained 30% of the variance in utterances f0. Cues and concerns were on average 13.07 Hz higher than neutral statements (p = 0.02). Cues and concerns in these consultations contained content with a high proportion of recurrence fears. Conclusion:The present study highlights the benefits and challenges of adding f0 and potential other prosodic features to the toolkit of coding emotional distress in the health communication setting. Practice implications:The assessment of f0 during clinical conversations can provide additional information for research into emotional expression.3

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Section: Discussionsupporting

confidence: 51%

Section: Fundamental Frequency Of Pitch (F0)mentioning

confidence: 99%

Using fundamental frequency of cancer survivors’ speech to investigate emotional distress in out-patient visits

Kandsberger

Rogers

Zhou

et al. 2016

Patient Education and Counseling

View full text Add to dashboard Cite

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“…For example, testing children requires special consideration, and experimental tasks must be specially designed to suit younger minds, most often by having them play games. There are many quite sophisticated examples of gamelike experiments for children, including "Dragon Master" (Metcalfe, Kornell, & Finn, 2009), "Frog Game" (Dunbar, Hill, & Lewis, 2001), and spaceships (Spencer & Hund, 2002, 2003; for more examples, see Berger, Jones, Rothbart, & Posner, 2000;Droit-Volet, Tourret, & Wearden, 2004;Kujala, Richardson, & Lyytinen, 2010;Ploog, Banerjee, & Brooks, 2009;Stevenson, Sundqvist, & Mahmut, 2007;Yildirim, Narayanan, & Potamianos, 2011). Other researchers working with children have simply presented an unaltered experimental task to the child as if it were a game.…”

Section: Introductionmentioning

confidence: 99%

Gamelike features might not improve data

et al. 2012

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Many psychological experiments require participants to complete lots of trials in a monotonous task, which often induces boredom. An increasingly popular approach to alleviate such boredom is to incorporate gamelike features into standard experimental tasks. Games are assumed to be interesting and, hence, motivating, and better motivated participants might produce better data (with fewer lapses in attention and greater accuracy). Despite its apparent prevalence, the assumption that gamelike features improve data is almost completely untested. We test this assumption by presenting a choice task and a change detection task in both gamelike and standard forms. Response latency, accuracy, and overall task performance were unchanged by gamelike features in both experiments. We present a novel cognitive model for the choice task, based on particle filtering, to decorrelate the dependent variables and measure performance in a more psychologically meaningful manner. The model-based analyses are consistent with the hypothesis that gamelike features did not alter cognition. A postexperimental questionnaire indicated that the gamelike version provided a more positive and enjoyable experience for participants than the standard task, even though this subjective experience did not translate into data effects. Although our results hold only for the two experiments examined, the gamelike features we incorporated into both tasks were typical of-and at least as salient and interesting as those usually used by-experimental psychologists. Our results suggest that modifying an experiment to include gamelike features, while leaving the basic task unchanged, may not improve the quality of the data collected, but it may provide participants with a better experimental experience.

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“…As an intermediate, elicitation and Wizard-Of-Oz methods (WOZ) can be used to collect (semi-)spontaneous emotional speech. Elicitation methods include watching movie clips (e.g., Lang [102]), listening to music (e.g., Wagner et al [204]), and playing games (e.g., Kim et al [91], Johnstone [88], Yildirim et al [216], Merkx et al [118], Truong et al [191]). Wizard-Of-Oz methods include interaction with a virtual character (e.g., Cox [46]) or spoken dialog system, see e.g., Ang et al [6], Batliner et al [16,15].…”

Section: Data Acquisition and Annotationmentioning

confidence: 99%

How does real affect affect affect recognition in speech?

Truong¹

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Detecting emotional state of a child in a conversational computer game

Cited by 81 publications

References 33 publications

Using fundamental frequency of cancer survivors’ speech to investigate emotional distress in out-patient visits

Using fundamental frequency of cancer survivors’ speech to investigate emotional distress in out-patient visits

Gamelike features might not improve data

How does real affect affect affect recognition in speech?

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