# Mirroring to Build Trust in Digital Assistants

arXiv: https://arxiv.org/abs/1904.01664 · HTML: https://mlsanity.com/paper/1904.01664/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 2 Apr 2019.

## Built on by (most cited first, 2 of 2)

- [FedEmbed: Personalized Private Federated Learning](https://mlsanity.com/paper/2202.09472/) (2022)
- [Implicit Design Choices and Their Impact on Emotion Recognition Model Development and Evaluation](https://mlsanity.com/paper/2309.03238/) (2023)

## Abstract (arXiv)

We describe experiments towards building a conversational digital assistant that considers the preferred conversational style of the user. In particular, these experiments are designed to measure whether users prefer and trust an assistant whose conversational style matches their own. To this end we conducted a user study where subjects interacted with a digital assistant that responded in a way that either matched their conversational style, or did not. Using self-reported personality attributes and subjects' feedback on the interactions, we built models that can reliably predict a user's preferred conversational style.