Application of Fuzzy Neural Network in Teaching Spoken English for Tourism

Abstract

Teaching spoken English for tourism is a skill everyone in the tourism industry needs. English is the international language of tourism, and communicating effectively with visitors is essential for providing excellent customer service and creating positive experiences. Students may not have regular access to native English speakers, making practice and improvement of spoken English difficult. Students may not encounter various real-world situations in the classroom, which can impair their communication ability. In this research, we present the development of an interactive language learning platform using a fuzzy neural network (FNN) to teach spoken English for tourism. This platform could include a chatbot or virtual assistant that understands and responds to spoken English inquiries from tourists using fuzzy neural networks. FNNs are used to teach spoken English for tourism using student data, and the work process involves evaluating each student's language proficiency, gathering and preprocessing data, training the network, assessing its performance, integrating it into a tailored language learning platform, and regularly providing feedback and correction to help students improve their spoken English abilities. The paired T-test was utilized to measure and assess the student's English listening and speaking abilities. The data package SPSS22.0 used to be the tool for information analysis, and statistics. Teachers can use FNN to improve language learning and prepare students for tourist sector conditions.