# If I Hear You Correctly: Building and Evaluating Interview Chatbots with Active Listening Skills

arXiv: https://arxiv.org/abs/2002.01862 · HTML: https://mlsanity.com/paper/2002.01862/

## Key facts

- Cited by 20 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 5 Feb 2020.

## Built on by (most cited first, 20 of 20)

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- [Comparing How a Chatbot References User Utterances from Previous Chatting Sessions: An Investigation of Users' Privacy Concerns and Perceptions](https://mlsanity.com/paper/2308.04879/) (2023)
- [A Novel Nuanced Conversation Evaluation Framework for Large Language Models in Mental Health](https://mlsanity.com/paper/2403.09705/) (2024)
- [Understanding Communication Preferences of Information Workers in Engagement with Text-Based Conversational Agents](https://mlsanity.com/paper/2410.20468/) (2024)
- [Inform the uninformed: Improving Online Informed Consent Reading with an AI-Powered Chatbot](https://mlsanity.com/paper/2302.00832/) (2023)
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- [Feedback by Design: Understanding and Overcoming User Feedback Barriers in Conversational Agents](https://mlsanity.com/paper/2602.01405/) (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)
- [Exploring the Human-LLM Synergy in Advancing Theory-driven Qualitative Analysis](https://mlsanity.com/paper/2405.05758/) (2024)
- [Interview AI-ssistant: Designing for Real-Time Human-AI Collaboration in Interview Preparation and Execution](https://mlsanity.com/paper/2504.13847/) (2025)
- [The Bots of Persuasion: Examining How Conversational Agents' Linguistic Expressions of Personality Affect User Perceptions and Decisions](https://mlsanity.com/paper/2602.17185/) (2026)
- [Synthetic Users, Real Differences: an Evaluation Framework for User Simulation in Multi-Turn Conversations](https://mlsanity.com/paper/2605.02624/) (2026)
- [Towards Automated Psychotherapy via Language Modeling](https://mlsanity.com/paper/2104.10661/) (2021)
- [Chaplains' Reflections on the Design and Usage of AI for Conversational Care](https://mlsanity.com/paper/2602.04017/) (2026)
- [AInterviewer: A Platform for Designing and Conducting AI-led Qualitative Interviews](https://mlsanity.com/paper/2606.20588/) (2026)
- [DeepSAGE: Stage-Aware Reinforcement Learning for Structured CBT Counseling Dialogue](https://mlsanity.com/paper/2608.22615/) (2026)

## Abstract (arXiv)

Interview chatbots engage users in a text-based conversation to draw out their views and opinions. It is, however, challenging to build effective interview chatbots that can handle user free-text responses to open-ended questions and deliver engaging user experience. As the first step, we are investigating the feasibility and effectiveness of using publicly available, practical AI technologies to build effective interview chatbots. To demonstrate feasibility, we built a prototype scoped to enable interview chatbots with a subset of active listening skills - the abilities to comprehend a user's input and respond properly. To evaluate the effectiveness of our prototype, we compared the performance of interview chatbots with or without active listening skills on four common interview topics in a live evaluation with 206 users. Our work presents practical design implications for building effective interview chatbots, hybrid chatbot platforms, and empathetic chatbots beyond interview tasks.