A Survey on Intelligent Speech Assistants: Architectures, Applications, and a Prototype for Weather Query

Xianzhen Li; Tao Sun; Zhenran Zhu

doi:10.54254/2755-2721/2025.28125

Applied and Computational EngineeringOpen access

A Survey on Intelligent Speech Assistants: Architectures, Applications, and a Prototype for Weather Query

Research Article

Open Access

A Survey on Intelligent Speech Assistants: Architectures, Applications, and a Prototype for Weather Query

Xianzhen Li ^1* Tao Sun ², Zhenran Zhu ³

¹ Artificial Intelligence, Wuhan Technical University, Wuhan, China

² Artificial Intelligence, Wuhan Technical University, Wuhan, China

³ Artificial Intelligence, Wuhan Technical University, Wuhan, China

^*Corresponding author: 564335sally@gmail.com

Published on 22 October 2025

ACE Vol.197

ISSN (Print): 2755-273X

ISSN (Online): 2755-2721

ISBN (Print): 978-1-80590-465-6

ISBN (Online): 978-1-80590-466-3

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Abstract

Intelligent speech assistants, as a representative application of artificial intelligence and big data, have been widely adopted in domains such as mobile devices, smart homes, education, and healthcare. This paper presents a comprehensive survey of recent research on speech assistants, focusing on their core architectures, key technologies (automatic speech recognition, natural language understanding, dialogue management, and text-to-speech), and representative application scenarios. The challenges of privacy protection, multilingual support, personalization, and low-resource optimization are also analyzed. To further demonstrate the practical aspects of speech assistants, we implement a lightweight prototype for weather query based on speech recognition, natural language processing, and text-to-speech synthesis. Experimental results show that the prototype can effectively support real-time user interaction, which verifies the feasibility of combining big data services with intelligent assistants. Finally, future research directions are discussed, including integration with large language models, multimodal interaction, and edge-cloud collaboration. This study provides both a systematic literature review and an exploratory case study, offering insights for the development and optimization of speech assistant systems in the era of big data.

Keywords:

Speech Assistant, Big Data, Speech Recognition, Natural Language Processing, Text-to-Speech

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References

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References

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Cite this article

Li,X.;Sun,T.;Zhu,Z. (2025). A Survey on Intelligent Speech Assistants: Architectures, Applications, and a Prototype for Weather Query. Applied and Computational Engineering,197,21-27.

Data availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

About volume

Volume title: Proceedings of the 7th International Conference on Computing and Data Science

ISBN: 978-1-80590-465-6(Print) / 978-1-80590-466-3(Online)

Editor: Marwan Omar

Conference website: https://2025.confcds.org/

Conference date: 25 September 2025

Series: Applied and Computational Engineering

Volume number: Vol.197

ISSN: 2755-2721(Print) / 2755-273X(Online)

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