Abstract
The ultimate goal of English teaching is to cultivate the students’ ability to communicate information in English, master good language learning methods, and become independent language learners and users. Therefore, successful English language teaching needs to be achieved through language communication training between teachers and students and between students. This article investigates the importance of promoting the reform of oral English teaching in China’s English teaching environment. We believe that to promote the reform of oral English teaching, an oral teaching environment must be available. However, the current common problem in oral English teaching in colleges and universities is that the spoken conversation objects are not standard enough, or there is no person who can talk to. Therefore, an intelligent spoken dialogue system based on big data and neural network technology is particularly important, and the quality of dialogue depends on accurate spoken speech evaluation. We first extracted six features of pronunciation quality, fluency, content richness, topic relevance, grammar, and vocabulary richness. Secondly, we propose an evaluation model that connects specific TDNN layers in a feedforward manner, using the feature representation of target words in different TDNN layers, which can obtain richer context information and greatly reduce the amount of model parameters. Finally, we conducted a simulation experiment. The experimental results show that the proposed model is accurate in evaluating spoken English and can effectively assist the reform of spoken English teaching in colleges and universities, and its performance is better than SVM by 9.2%.
Highlights
In recent years, the application of information technology [1,2,3] in the field of education is more and more extensive
Based on the foregoing observations, we discovered that big data and deep neural network technology-driven college oral English teaching reforms [23, 24] have become a trend
An intelligent oral dialogue system based on big data and neural network technology is critical, and the quality of discourse is dependent on precise oral evaluation
Summary
The application of information technology [1,2,3] in the field of education is more and more extensive. In oral English teaching, due to the increasing popularity of English teaching in China, traditional language teaching methods [4] can no longer meet people’s needs, which is more and more obvious in colleges and universities In this context, the computer-aided language learning system [5,6,7] based on big data and neural network [8,9,10] has become the focus of research. The computer-aided language learning system [5,6,7] based on big data and neural network [8,9,10] has become the focus of research It can take the place of teachers for students’ examination answers, classroom homework automation correction, so that teachers from repeated and time-consuming correction work out of the liberation. The system can greatly facilitate people’s daily life and, at the same time, improve work efficiency to a large extent
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
