Year: 2025
Type: article
Abstract: Voice-controlled infotainment systems represent a transformative advancement in automotive technology, significantly enhancing accessibility for drivers with disabilities and improving all users' safety. These sophisticated systems leverage speech recognition algorithms and natural language processing capabilities to interpret verbal commands and execute corresponding functions across vehicle systems. The evolution from basic command recognition to conversational interfaces has enabled more natural interactions that accommodate diverse speech patterns, accents, and languages. Key components, including acoustic signal processing, speech recognition engines, natural language understanding modules, dialog management systems, and text-to-speech synthesis, work in concert to deliver responsive experiences even in challenging acoustic environments. Personalized voice profiles, hearing aid integration, multilingual support, and adaptive learning algorithms address specific accessibility needs for users with various disabilities. Safety benefits emerge from reduced visual and manual distractions, with techniques such as progressive disclosure, contextual awareness, and graduated feedback mechanisms minimizing cognitive load. Future directions include emotion recognition capabilities, deeper integration with autonomous driving features, and enhanced edge processing, while standardization, compatibility, and privacy challenges require ongoing attention. The continued advancement of these systems represents a rare technological convergence that simultaneously enhances safety, convenience, and accessibility, creating more equitable mobility solutions.
Author: Ravinder Katla
Institution: General Motors (United States)
Language: English
Topic: Speech and dialogue systems
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W4408678477