学科知识图谱引导的智能化英语语音教学平台构建研究

Research on the Construction of an Intelligent English Phonetics Teaching Platform Guided by Disciplinary Knowledge Graph

摘要: 在高校英语教育数字化转型的背景下，传统英语语音教学长期存在知识体系碎片化、教材内容分散、反馈机制滞后、个性化学习支持不足等问题，难以满足学生系统化、自主化语音学习的现实需求。本研究以语言学与教育技术学交叉融合为视角，提出将学科知识图谱与智能语音技术相结合，构建集语音知识学习、技能训练、发音纠正、学习社区、水平测试于一体的智能化英语语音学习平台的设计方案。研究围绕英语语音知识本体建模、多模态资源整合、图数据库构建、智能测评与个性化推荐等关键环节展开理论设计与技术路径探索，重点阐述平台整体架构、功能模块与实现思路。本研究并非基于已完成系统的实证研究，而是面向未来教学需求提出的可行性技术方案与创新构想，旨在为高校英语语音教学数字化、智能化改革提供理论参考与实践框架，推动“外语 + AI”复合型教学模式的探索与发展。

Abstract: Against the backdrop of the digital transformation of college English education, traditional English phonetics teaching has long been plagued by problems such as fragmented knowledge systems, scattered textbook contents, delayed feedback mechanisms, and insufficient support for personalized learning. These issues make it difficult to meet students’ practical needs for systematic and autonomous phonetics learning. From the interdisciplinary perspective of linguistics and educational technology, this study proposes an integrated design scheme that combines disciplinary knowledge graphs with intelligent speech technologies to build an intelligent English phonetics learning platform, which integrates phonetics knowledge learning, skill training, pronunciation correction, learning community interaction, and proficiency assessment. The research explores theoretical designs and technical paths around key links including ontology modeling of English phonetics knowledge, multimodal resource integration, graph database construction, intelligent assessment, and personalized recommendation, with a focus on elaborating the overall architecture, functional modules, and implementation ideas of the platform. Rather than an empirical study based on a completed system, this research puts forward a feasible technical solution and innovative conception oriented to future teaching demands. It aims to provide theoretical references and practical frameworks for the digital and intelligent reform of college English phonetics teaching, and promote the exploration and development of the “foreign language + AI” interdisciplinary teaching model.