This study explores linguistic distinctions among American, Indian, and Irish English dialects and assesses various Language Models (LLMs) in their ability to generate British English translations from these dialects. Using cosine similarity analysis, the study measures the linguistic proximity between original British English translations and those produced by LLMs for each dialect. The findings reveal that Indian and Irish English translations maintain notably high similarity scores, suggesting strong linguistic alignment with British English. In contrast, American English exhibits slightly lower similarity, reflecting its distinct linguistic traits. Additionally, the choice of LLM significantly impacts translation quality, with Llama-2-70b consistently demonstrating superior performance. The study underscores the importance of selecting the right model for dialect translation, emphasizing the role of linguistic expertise and contextual understanding in achieving accurate translations.

该研究探讨了美国英语、印度英语和爱尔兰英语的语言差异，并评估了各种语言模型在从这些方言生成英式英语翻译方面的能力。研究使用余弦相似度分析来衡量原始英式英语翻译与语言模型为每种方言生成的翻译之间的语言接近程度。研究结果显示，印度英语和爱尔兰英语翻译保持了显著高的相似度得分，表明与英式英语具有很强的语言对齐性。相比之下，美国英语的相似度稍低，反映出其独特的语言特征。此外，语言模型的选择显著影响翻译质量，其中Llama-2-70b始终表现出卓越的性能。该研究强调了选择方言翻译的正确模型的重要性，强调语言专业知识和情境理解在实现准确翻译中的作用。

跨方言句子转换：适应英国英语的语言模型的比较分析