英语语音识别系统的方言适应性研究  

Research on Dialect Adaptability of English Speech Recognition System

作　　者：李想 Xiang Li(Chengdu College of University of Electronic Science and Technology of China,Chengdu,Sichuan 610000)

机构地区：[1]电子科技大学成都学院,四川成都610000

出　　处：《教育思想理论研究》2025年第4期109-111,共3页Research on Educational Thought Theory

摘　　要：本文深入探究了英语语音识别系统在不同方言环境下的适应性,详细剖析了方言差异对语音识别准确率的具体影响,并针对性地提出了一系列切实可行的优化措施,旨在全面提升系统的方言识别能力。本研究通过实验手段,广泛采集了多种英语方言的语音资料,对现有系统的识别能力进行了全面测试,并深入评估了算法优化后的实际成效。研究结果表明,方言间存在的显著差异对语音识别的精准度产生了显著影响。但幸运的是,通过运用先进的数据增强技术、迁移学习策略以及深度神经网络的优化手段,我们成功地大幅提升了系统对方言的适应能力。此项研究不仅奠定了构建更具包容性的语音识别技术的理论基础,更为实际操作提供了详尽的指南。This article delves into the adaptability of English speech recognition systems in different dialect environments,analyzes in detail the specific impact of dialect differences on speech recognition accuracy,and proposes a series of practical optimization measures aimed at comprehensively improving the system's speech recognition capabilities.This study extensively collected speech data from various English dialects through experimental methods,comprehensively tested the recognition ability of existing systems,and thoroughly evaluated the actual effectiveness of algorithm optimization.The research results indicate that significant differences between dialects have a significant impact on the accuracy of speech recognition.Fortunately,by utilizing advanced data augmentation techniques,transfer learning strategies,and optimization methods of deep neural networks,we have successfully significantly improved the system's adaptability to dialects.This study not only lays the theoretical foundation for building more inclusive speech recognition technology,but also provides detailed guide⁃lines for practical operation.

关 键 词：英语语音识别 方言适应性 语音处理 深度学习 数据增强 

分 类 号：H31[语言文字—英语]