The construction of Bert fusion model of speech recognition and sensing for South China electricity charge service scenario

IF 1.7 4区 工程技术 Q3 ENGINEERING, ELECTRICAL & ELECTRONIC Eurasip Journal on Advances in Signal Processing Pub Date : 2023-11-06 DOI:10.1186/s13634-023-01073-4
Guangcai Wu, Yinglong Zheng
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Abstract

Abstract Electric charge service and management is an important part of electric power work. The effective recovery of the electric charge relates to the smooth development of daily work and continuous improvement of the operation and management of power supply enterprises. With the large-scale implementation of the card prepayment system, the problem of electricity customers defaulting on electricity charges has been solved to a large extent, but some large electricity users still fail to pay electricity charges on time. Therefore, under the current situation of power grid development, it is still necessary to strengthen the service and management of electricity charges to promote efficient recovery of electricity charges. Speech recognition technology has increasingly become the focus of research institutions at home and abroad. People are committed to enabling machines to understand human speech instructions and hope to control the machine through speech. The research and development of speech recognition will greatly facilitate people's lives shortly. The development of 5G technology and the proposal of 6G technology make the interconnection of all things not only a hope but also a reality. To realize the interconnection of all things, one of the key technical breakthroughs is the development of a new human–computer interaction sensing system. Under the guidance of relevant theories and methods, this paper systematically analyzes the user structure, electricity charge recovery management and service system, existing problems and causes in South China, and clarifies the necessity of design and application of electricity charge service system in South China power supply companies. The experimental data and empirical analysis results show that the optimized Bert fusion model can provide more digital support for the power supply companies in South China in terms of electricity charge recovery efficiency, management level system improvement, and electricity charge service.

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华南收费服务场景语音识别与传感Bert融合模型的构建
收费服务与管理是电力工作的重要组成部分。电费的有效回收关系到供电企业日常工作的顺利开展和经营管理的不断改进。随着卡预付费系统的大规模实施,用电客户拖欠电费的问题在很大程度上得到了解决,但部分用电大户仍未按时缴纳电费。因此,在电网发展的现状下,仍需加强对电费的服务和管理,促进电费的高效回收。语音识别技术日益成为国内外研究机构关注的焦点。人们致力于使机器能够理解人类的语音指令,并希望通过语音来控制机器。语音识别技术的研究和发展将在不久的将来为人们的生活带来极大的便利。5G技术的发展和6G技术的提出,使得万物互联不仅是希望,更是现实。实现万物互联,关键技术突破之一是开发新型人机交互传感系统。本文在相关理论和方法的指导下,系统分析了华南地区的用户结构、电费回收管理与服务体系、存在的问题和原因,阐明了华南供电企业设计和应用电费服务系统的必要性。实验数据和实证分析结果表明,优化后的Bert融合模型能够在电费回收效率、管理水平体系提升、电费服务等方面为华南供电企业提供更多的数字化支持。
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来源期刊
Eurasip Journal on Advances in Signal Processing
Eurasip Journal on Advances in Signal Processing ENGINEERING, ELECTRICAL & ELECTRONIC-
CiteScore
3.40
自引率
10.50%
发文量
109
审稿时长
3-8 weeks
期刊介绍: The aim of the EURASIP Journal on Advances in Signal Processing is to highlight the theoretical and practical aspects of signal processing in new and emerging technologies. The journal is directed as much at the practicing engineer as at the academic researcher. Authors of articles with novel contributions to the theory and/or practice of signal processing are welcome to submit their articles for consideration.
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