Understanding the Architecture of Voice Assistants: A Technical Deep Dive

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.

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Publication Details

Journal
International Journal of Scientific Research in Computer Science Engineering and Information Technology
Published
2025-03-05
DOI
https://doi.org/10.32628/cseit25112398
Primary Topic
AI in Service Interactions
Type
article
Field-Weighted Citation Impact
0.00
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article

Understanding the Architecture of Voice Assistants: A Technical Deep Dive

Velpuri Venkata Satya Sai Sriram
International Journal of Scientific Research in Computer Science Engineering and Information Technology
AI in Service Interactions
article

Understanding the Architecture of Voice Assistants: A Technical Deep Dive

Velpuri Venkata Satya Sai Sriram
article en

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.

International Journal of Scientific Research in Computer Science Engineering and Information TechnologyVol. 11(2)
Carnegie Mellon University (US)
Openalex Percentile: Top 98%
AI in Service Interactions
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