用情感与语义分析评估谷歌翻译中文译文质量，发现其存在理解偏差。
Evaluation of Google Translate for Mandarin Chinese translation using sentiment and semantic analysis
- 通过情感和语义分析对比谷歌翻译与人工译本
- 谷歌翻译在语义和情感精度上均低于人工译本
- 对中文典故等文化特定内容翻译能力不足
大型语言模型（LLMs）的机器翻译正产生深远全球影响，使交流更加便捷。普通话是中国政府与媒体的官方沟通语言。本研究提出一种自动化评估框架，对比谷歌翻译与人工专家译本的翻译质量，基于情感与语义分析。为验证该框架，选取20世纪初经典小说《阿Q正传》中的部分中译英文本，使用谷歌翻译生成英文版本，并进行逐章情感分析与语义分析，比较不同译本提取的情感分布。结果表明，谷歌翻译在语义和情感分析上的精确度均低于人工译本。研究发现，谷歌翻译无法准确处理部分中文特有表达，如传统典故，原因可能在于缺乏对中国语境与历史背景的理解。
原文摘要 · Abstract (English)
Machine translation using large language models (LLMs) is having a significant global impact, making communication easier. Mandarin Chinese is the official language used for communication by the government and media in China. In this study, we provide an automated assessment of translation quality of Google Translate with human experts using sentiment and semantic analysis. In order to demonstrate our framework, we select the classic early twentieth-century novel 'The True Story of Ah Q' with selected Mandarin Chinese to English translations. We use Google Translate to translate the given text into English and then conduct a chapter-wise sentiment analysis and semantic analysis to compare the extracted sentiments across the different translations. Our results indicate that the precision of Google Translate differs both in terms of semantic and sentiment analysis when compared to human expert translations. We find that Google Translate is unable to translate some of the specific words or phrases in Chinese, such as Chinese traditional allusions. The mistranslations may be due to lack of contextual significance and historical knowledge of China.
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