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

Abstract

AbstractElectric 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.