# Alexa as an Active Listener: How Backchanneling Can Elicit Self-Disclosure and Promote User Experience

arXiv: https://arxiv.org/abs/2204.10191 · HTML: https://mlsanity.com/paper/2204.10191/

## Key facts

- Cited by 6 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 21 Apr 2022.

## Built on by (most cited first, 6 of 6)

- [The Pursuit of Empathy: Evaluating Small Language Models for PTSD Dialogue Support](https://mlsanity.com/paper/2505.15065/) (2025)
- [Expressivity and Speech Synthesis](https://mlsanity.com/paper/2404.19363/) (2024)
- [F-Actor: Controllable Conversational Behaviour in Full-Duplex Models](https://mlsanity.com/paper/2601.11329/) (2026)
- [Hear You in Silence: Designing for Active Listening in Human Interaction with Conversational Agents Using Context-Aware Pacing](https://mlsanity.com/paper/2602.06134/) (2026)
- [Challenges and Opportunities for the Design of Smart Speakers](https://mlsanity.com/paper/2306.05741/) (2023)
- [DiffListener: Discrete Diffusion Model for Listener Generation](https://mlsanity.com/paper/2502.06822/) (2025)

## Abstract (arXiv)

Active listening is a well-known skill applied in human communication to build intimacy and elicit self-disclosure to support a wide variety of cooperative tasks. When applied to conversational UIs, active listening from machines can also elicit greater self-disclosure by signaling to the users that they are being heard, which can have positive outcomes. However, it takes considerable engineering effort and training to embed active listening skills in machines at scale, given the need to personalize active-listening cues to individual users and their specific utterances. A more generic solution is needed given the increasing use of conversational agents, especially by the growing number of socially isolated individuals. With this in mind, we developed an Amazon Alexa skill that provides privacy-preserving and pseudo-random backchanneling to indicate active listening. User study (N = 40) data show that backchanneling improves perceived degree of active listening by smart speakers. It also results in more emotional disclosure, with participants using more positive words. Perception of smart speakers as active listeners is positively associated with perceived emotional support. Interview data corroborate the feasibility of using smart speakers to provide emotional support. These findings have important implications for smart speaker interaction design in several domains of cooperative work and social computing.