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

TL;DR

This research investigates users' emotional responses, especially confusion, during voice-based human-machine interactions, focusing on communication errors through two experimental studies involving audio-visual data and self-reports.

Contribution

It provides new insights into affective states during voice interactions, emphasizing confusion's role in communication failures, with comprehensive analysis of observational and self-reported data.

Findings

Confusion is a prominent affective state during communication failures.

Self-reports and observations reveal different patterns of affective responses.

Communication errors significantly impact user affective states.

Abstract

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.