Abstract
Abstract This research delves into the impact of affective expressions in spoken English, aiming to enhance spoken language teaching through corpus analysis. Recognizing English’s status as a global lingua franca, this study emphasizes the pivotal role of emotion in communication. By constructing a comprehensive spoken corpus, we uncover patterns in affective expressions to inform teaching strategies, thereby boosting oral competencies. Our methodology combines quantitative and qualitative approaches, analyzing 56,253.86 minutes of speech to create a diverse and systematic dataset. Results reveal a strong link between affective expression use and improved speaking skills, with users showing a notable accuracy increase in tests. Furthermore, implementing a multimodal teaching approach significantly alleviated speaking anxiety among learners. These findings underscore the importance of emotional expressions in enhancing communicative effectiveness and reducing language-related anxiety, offering significant implications for English education.
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