Towards Understanding Confusion and Affective States Under Communication Failures in Voice-Based Human-Machine Interaction

We present a series of two studies conducted to understand user's affective states during voice-based human-machine interactions. Emphasis is placed on the cases of communication errors or failures. In particular, we are interested in understanding "confusion" in relation with other a...

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Bibliographic Details
Published in2021 9th International Conference on Affective Computing and Intelligent Interaction Workshops and Demos (ACIIW) pp. 1 - 5
Main Authors Kim, Sujeong, Garlapati, Abhinav, Lubin, Jonah, Tamrakar, Amir, Divakaran, Ajay
Format Conference Proceeding
LanguageEnglish
Published IEEE 28.09.2021
Subjects
Affective computing
affective dataset
Conferences
confusion
human-computer communication
Man-machine systems
multimodal data
Problem-solving
Task analysis
voice-based interface
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Summary:We present a series of two studies conducted to understand user's affective states during voice-based human-machine interactions. Emphasis is placed on the cases of communication errors or failures. In particular, we are interested in understanding "confusion" in relation with other affective states. The studies consist of two types of tasks: (1) related to communication with a voice-based virtual agent: speaking to the machine and understanding what the machine says, (2) non-communication related, problem-solving tasks where the participants solve puzzles and riddles but are asked to verbally explain the answers to the machine. We collected audio-visual data and self-reports of affective states of the participants. We report results of two studies and analysis of the collected data. The first study was analyzed based on the annotator's observation, and the second study was analyzed based on the self-report.
DOI:10.1109/ACIIW52867.2021.9666238