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New framework "Speak to the City" uses gaze and language to identify vehicle landmarks

By PulseAugur Editorial · [2 sources] ·

Researchers have developed a new framework called "Speak to the City" to improve how passengers in vehicles query physical landmarks. This system fuses user gaze with natural language to identify Points of Interest, addressing challenges like ego-motion and referential ambiguity. A user study involving 46 participants mapped head orientation into a 3D digital twin, capturing gaze-speech behaviors. A lightweight Transformer network was trained using LLMs to align spatial gaze with verbal context, achieving 83.33% Top-1 accuracy with an average inference time of 24.3 milliseconds. AI

IMPACT This research could enhance in-car AI experiences by enabling more intuitive and accurate interactions with the physical environment.

RANK_REASON The cluster contains a research paper detailing a new framework and experimental results.

Read on arXiv cs.CL →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

New framework "Speak to the City" uses gaze and language to identify vehicle landmarks

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COVERAGE [2]

  1. arXiv cs.CL TIER_1 English(EN) · Alireza Parchami (Mercedes-Benz Tech Innovation GmbH, Saarland University), Artin Saberpour (Saarland University), Robin Connor Schramm (Mercedes-Benz Tech Innovation GmbH, RheinMain University of Applied Sciences), J\"urgen Steimle (Saarland University)… ·

    Speak to the City: Multimodal Resolution for Outside-the-Vehicle References

    arXiv:2609.14691v1 Announce Type: cross Abstract: As autonomous vehicles and Extended Reality (XR) headsets enable novel in-car interactions, seamlessly querying physical landmarks, known as Outside-the-Vehicle Referencing (OVR), remains challenging due to ego-motion and referent…

  2. arXiv cs.IR (Information Retrieval) TIER_1 English(EN) · Ulrich Schwanecke ·

    Speak to the City: Multimodal Resolution for Outside-the-Vehicle References

    As autonomous vehicles and Extended Reality (XR) headsets enable novel in-car interactions, seamlessly querying physical landmarks, known as Outside-the-Vehicle Referencing (OVR), remains challenging due to ego-motion and referential ambiguity. We present a robust, multimodal OVR…

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