A Survey on the Evolution and Future Directions of Intelligent Voice Assistants: Advances, Drawbacks, and Motivations for Next-Generation Systems

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Abstract

Artificial intelligence (AI) advances have spurred intelligent voice assistants (IVAs), significantly transforming human-machine interaction paradigms. This paper surveys the evolution and future directions of this field, motivating the development of next-generation systems. We focus on designs integrating machine learning (ML), natural language processing (NLP), and speech recognition to deliver highly responsive, interactive, and adaptive user experiences. Unlike basic IVAs limited to predefined commands, advanced systems utilize modular architectures enabling dynamic task execution, including application management, system control, real-time web/multimedia search, and versatile content generation (in formats like PDF, Word, Excel, PPT, TXT). This work aims to contribute toward IVAs capable of autonomous reasoning, making AI interaction profoundly more intuitive, efficient, and human-centric.

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