# Analysis and Detection of Differences in Spoken User Behaviors between Autonomous and Wizard-of-Oz Systems

arXiv: https://arxiv.org/abs/2410.03147 · HTML: https://mlsanity.com/paper/2410.03147/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 2 of its 26 references that are in the map.
- First posted on arXiv 4 Oct 2024.

## Builds on (most cited first, 2 of 2)

- [Survey on Evaluation Methods for Dialogue Systems](https://mlsanity.com/paper/1905.04071/) (2019)
- [An Analysis of User Behaviors for Objectively Evaluating Spoken Dialogue Systems](https://mlsanity.com/paper/2401.04867/) (2024)

## Built on by (most cited first, 1 of 1)

- [Does the Appearance of Autonomous Conversational Robots Affect User Spoken Behaviors in Real-World Conference Interactions?](https://mlsanity.com/paper/2503.13625/) (2025)

## Abstract (arXiv)

This study examined users' behavioral differences in a large corpus of Japanese human-robot interactions, comparing interactions between a tele-operated robot and an autonomous dialogue system. We analyzed user spoken behaviors in both attentive listening and job interview dialogue scenarios. Results revealed significant differences in metrics such as speech length, speaking rate, fillers, backchannels, disfluencies, and laughter between operator-controlled and autonomous conditions. Furthermore, we developed predictive models to distinguish between operator and autonomous system conditions. Our models demonstrated higher accuracy and precision compared to the baseline model, with several models also achieving a higher F1 score than the baseline.