Understanding the Architecture of Voice Assistants: A Technical Deep Dive
Year: 2025
Type: article
Abstract: This comprehensive article explores the evolution of voice assistant technologies and their current state, examining their architectural components, performance metrics, and integration challenges. The article investigates various aspects, including speech recognition systems, natural language understanding capabilities, dialogue management, and system integration frameworks. The article synthesizes findings from multiple studies to provide insights into user adoption patterns, technical performance benchmarks, and the effectiveness of error-handling mechanisms. The article encompasses controlled environment testing and real-world applications, offering a holistic view of voice assistant capabilities across different operational contexts and use cases.
Author: Venkatesh Sriram
Institution: Carnegie Mellon University
Language: English
Topic: Speech and dialogue systems
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4408246741