mlsanityData to 14 Oct 2026

Evaluation of Google Translate for Mandarin Chinese translation using sentiment and semantic analysis

arXiv 2409.04964 ↗First posted 8 Sep 2024cs.CL cs.AIcited by 2

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Abstract (arXiv)

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.

Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 16 of its 100 references that are in the map. First posted on arXiv 8 Sep 2024.

Builds on

16 of 100 references.

References · 16

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4 more
  1. 2023An evaluation of Google Translate for Sanskrit to English translation via sentiment and semantic analysiscited by 6
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Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 1; 2026: 1.

2 papers.

  1. 2025HP-BERT: A framework for longitudinal study of Hinduphobia on social media via language modelscited by 1
  2. 2026Automated evaluation of LLMs for effective machine translation of Mandarin Chinese to Englishcited by 0