Quester: A Speech-based Question Answering Support System for Oral Presentations
Authors
Current slideware, such as PowerPoint, reinforces the delivery of linear oral presentations. In settings such as question answering sessions or review lectures, more extemporaneous and dynamic presentations are required. An intelligent system that can automatically identify and display the slides most related to the presenter’s speech, allows for more speaker flexibility in sequencing their presentation. We present Quester, a system that enables fast access to relevant presentation content during a question answering session and supports nonlinear presentations led by the speaker. Given the slides' contents and notes, the system ranks presentation slides based on semantic closeness to spoken utterances, displays the most related slides, and highlights the corresponding content keywords in slide notes. The design of our system was informed by findings from interviews with expert presenters and analysis of recordings of lectures and conference presentations. In a within-subjects study comparing our dynamic support system with a static slide navigation system during a question answering session, presenters expressed a strong preference for our system and answered the questions more efficiently using our system.
Research Questions / Practical Problems
Question signals indexed for this paper.
- 60%
To Type or To Speak? The Effect of Input Modality on Text Understanding During Note-taking
CHI '22· Voice User Interface (VUI) Design +1
- 60%
Exploring the Impact of Avatar Representations in AI Chatbot Tutors on Learning Experiences
CHI '25· Agent Personality & Anthropomorphism +1
- 60%
Classroom Simulacra: Building Contextual Student Generative Agents in Online Education for Learning Behavioral Simulation
CHI '25· Human-LLM Collaboration +1
- 60%
Exploring LLM-Powered Role and Action-Switching Pedagogical Agents for History Education in Virtual Reality
CHI '25· Social & Collaborative VR +1
- 60%
Good Fences Make Good Learning: How Self-Directed Language Learners Navigate LLM Delegation Decisions
CHI '26· Human-LLM Collaboration +1
- 60%
AskNow: An LLM-powered Interactive System for Real-Time Question Answering in Large-Scale Classrooms
CHI '26· Human-LLM Collaboration +1
- 60%
AI meets Mathematics Education: Supporting Instructors in Large Mathematics Classes with Context-Aware AI
CHI '26· Human-LLM Collaboration +1
- 60%
ClassComet: Exploring and Designing AI-generated Danmaku in Educational Videos to Enhance Online Learning
DIS '25· Human-LLM Collaboration +1
- 60%
Can an AI Partner Empower Learners to Ask Critical Questions?
IUI '25· Human-LLM Collaboration +1
Based on Jaccard similarity of research subtopics & professions (≥60%)