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LLM and Natural Language Interaction / In-Vehicle and Autonomous Driving Voice Assistant Contexts

Can multimodal data enable more accurate driving interaction timing prediction?

helpResearch questionIn-Vehicle and Autonomous Driving Voice Assistant Contexts

Can multimodal data enable more accurate driving interaction timing prediction?

UbiComp '21Learning When Agents Can Talk to Drivers Using the INAGT Dataset and Multisensor Fusion

Similar questions

helpResearch questionIn-Vehicle and Autonomous Driving Voice Assistant Contexts

Can dynamically adjusting voice command format effectively improve information processing and reaction efficiency while driving?

CHI '24AdaptiveVoice: Cognitively Adaptive Voice Interface for Driving Assistance

helpResearch questionIn-Vehicle and Autonomous Driving Voice Assistant Contexts

How do changes in users' cognitive load affect their preferences for different voice command formats?

CHI '24AdaptiveVoice: Cognitively Adaptive Voice Interface for Driving Assistance

helpResearch questionIn-Vehicle and Autonomous Driving Voice Assistant Contexts

Can combining cognitive-load-adaptive voice assistants with HUD (head-up display) further optimize the driving experience?

CHI '24AdaptiveVoice: Cognitively Adaptive Voice Interface for Driving Assistance

helpResearch questionIn-Vehicle and Autonomous Driving Voice Assistant Contexts

How do different dialogue domains (e.g., safety-related, comfort-oriented) shape prompt language design preferences for in-vehicle voice assistants?

CUI '23Secure, Comfortable or Functional: Exploring Domain-Sensitive Prompt Design for In-Car Voice Assistants

helpResearch questionIn-Vehicle and Autonomous Driving Voice Assistant Contexts

How do syntactic properties of prompt language (e.g., sentence structure, length, active vs. passive voice) affect user experience in in-vehicle voice assistants?

CUI '23Secure, Comfortable or Functional: Exploring Domain-Sensitive Prompt Design for In-Car Voice Assistants

helpResearch questionIn-Vehicle and Autonomous Driving Voice Assistant Contexts

Do conversation types (functional, informational, proactive) influence domain sensitivity in in-vehicle voice assistant prompt design?

CUI '23Secure, Comfortable or Functional: Exploring Domain-Sensitive Prompt Design for In-Car Voice Assistants

Related papers

AdaptiveVoice: Cognitively Adaptive Voice Interface for Driving Assistance

Shaoyue Wen, Songming Ping, Jialin Wang