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Augmented Conversation with Embedded Speech-Driven On-the-Fly Referencing in AR

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arxiv 2405.18537 v1 pith:YDBCHQVG submitted 2024-05-28 cs.HC cs.LG

Augmented Conversation with Embedded Speech-Driven On-the-Fly Referencing in AR

classification cs.HC cs.LG
keywords conversationreferencingaugmentedon-the-flyvisualconversationsdesignembedded
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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This paper introduces the concept of augmented conversation, which aims to support co-located in-person conversations via embedded speech-driven on-the-fly referencing in augmented reality (AR). Today computing technologies like smartphones allow quick access to a variety of references during the conversation. However, these tools often create distractions, reducing eye contact and forcing users to focus their attention on phone screens and manually enter keywords to access relevant information. In contrast, AR-based on-the-fly referencing provides relevant visual references in real-time, based on keywords extracted automatically from the spoken conversation. By embedding these visual references in AR around the conversation partner, augmented conversation reduces distraction and friction, allowing users to maintain eye contact and supporting more natural social interactions. To demonstrate this concept, we developed \system, a Hololens-based interface that leverages real-time speech recognition, natural language processing and gaze-based interactions for on-the-fly embedded visual referencing. In this paper, we explore the design space of visual referencing for conversations, and describe our our implementation -- building on seven design guidelines identified through a user-centered design process. An initial user study confirms that our system decreases distraction and friction in conversations compared to smartphone searches, while providing highly useful and relevant information.

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Cited by 4 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. ChatMuse: Supporting In-Person Small-Group Conversation Experience with a Proactive Assistive AI Agent in Mixed Reality

    cs.HC 2026-07 conditional novelty 6.0

    A proactive mixed-reality AI agent that privately suggests speech and nonverbal behavior can help one participant feel more engaged in small-group conversations, according to an 18-person within-subject study.

  2. VisionClaw: Always-On AI Agents through Smart Glasses

    cs.HC 2026-04 unverdicted novelty 5.0

    VisionClaw couples continuous egocentric vision on smart glasses with speech-driven AI agents to enable hands-free real-world tasks, with lab and field studies showing faster completion and a shift toward opportunisti...

  3. From Speech-to-Spatial: Grounding Utterances on A Live Shared View with Augmented Reality

    cs.HC 2026-02 unverdicted novelty 5.0

    Speech-to-Spatial parses spoken references into an object-centric graph to render persistent AR guidance, improving efficiency over voice-only baselines in remote assistance.

  4. Exploring Needs and Design Opportunities for Proactive Information Support in In-Person Small-Group Conversations

    cs.HC 2026-01 unverdicted novelty 5.0

    A preliminary participatory design study identifies design opportunities for proactive mixed reality information support to enhance engagement in in-person small-group conversations.