Design And Implementation Of English Audio Visual Application Based On React Native

Today,accompanied by the globalization of politics,economy and culture,the communication between people of different countries has become more and more common.Therefore,the demand for language learning in various countries has become larger and larger.English is the most widely used language in the world,and at present,English is regarded as the main foreign language learning subject in China since preschool education.In addition to school teaching,the third-party training institutions and interest classes also emerge in endlessly.And in today’s mobile Internet tide,a lot of English learning apps are born as well.According to the mobile Internet data research report for the second quarter of 2020 released by well-known domestic institutions,the popularity of apps in the short video industry continues to increase,and the average daily use time of video apps exceeds 83 minutes.This article proposes an online learning program that combines English learning with short videos.English learners use the program in the form of APP.This article will describe the design and implementation of APP in detail.The technical selection involved in this system is as follows:1.In terms of server architecture,the current relatively stable and reliable microservice architecture will be adopted.The advantage of this architecture is that the volume of each service is relatively small,business splitting is more reasonable and scientific,and the distributed deployment method allows the system Expansion becomes convenient and controllable.The microservice architecture adopted by this system is the Spring Cloud open-source solution,and the CI/CD solution is implemented using Kubernetes.2.The development of microservices involves many functions,and the related business logic is also more complicated.The main microservices include video coding,speech recognition and evaluation,user behaviour analysis and recommendation.The schemes used for video coding include Rabbit MQ message queue,FFmpeg multimedia coding tools,etc.;speech recognition will adopt online recognition schemes,and the technologies and tools used are Kaldi and Kaldi GStreamer Server;user behaviour collection microservices use Spring Boot open remote API Way to achieve.3.The client will be based on React Native’s high-performance Hybrid APP development solution,which can effectively solve mobile cross-platform problems without losing user experience.This article will complete an English audiovisual application based on React Native under the framework of the above technical solutions.The purpose of this application is to: solve the boring situation of individuals learning English alone;learn authentic English pronunciation from intuitive video scenes to improve speaking ability;combine interactive social interaction with learning to enrich the way of learning English;break time and space The constraints of the above,the use of fragmented learning methods to improve time utilization;after long-term iteration,a complete set of scientific learning models are formed,which can be transplanted to more language learning.