mlsanityData to 7 Oct 2026

An evaluation of Google Translate for Sanskrit to English translation via sentiment and semantic analysis

arXiv 2303.07201 ↗First posted 28 Feb 2023cs.CL cs.AIcited by 6

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Abstract (arXiv)

Google Translate has been prominent for language translation; however, limited work has been done in evaluating the quality of translation when compared to human experts. Sanskrit one of the oldest written languages in the world. In 2022, the Sanskrit language was added to the Google Translate engine. Sanskrit is known as the mother of languages such as Hindi and an ancient source of the Indo-European group of languages. Sanskrit is the original language for sacred Hindu texts such as the Bhagavad Gita. In this study, we present a framework that evaluates the Google Translate for Sanskrit using the Bhagavad Gita. We first publish a translation of the Bhagavad Gita in Sanskrit using Google Translate. Our framework then compares Google Translate version of Bhagavad Gita with expert translations using sentiment and semantic analysis via BERT-based language models. Our results indicate that in terms of sentiment and semantic analysis, there is low level of similarity in selected verses of Google Translate when compared to expert translations. In the qualitative evaluation, we find that Google translate is unsuitable for translation of certain Sanskrit words and phrases due to its poetic nature, contextual significance, metaphor and imagery. The mistranslations are not surprising since the Bhagavad Gita is known as a difficult text not only to translate, but also to interpret since it relies on contextual, philosophical and historical information. Our framework lays the foundation for automatic evaluation of other languages by Google Translate

Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). Builds on 24 of its 103 references that are in the map. First posted on arXiv 28 Feb 2023.

Builds on

24 of 103 references.

References · 24

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12 more
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Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 3; 2025: 2; 2026: 1.

6 papers.

  1. 2024Large language models for newspaper sentiment analysis during COVID-19: The Guardiancited by 4
  2. 2024Evaluation of Google Translate for Mandarin Chinese translation using sentiment and semantic analysiscited by 2
  3. 2025An evaluation of LLMs and Google Translate for translation of selected Indian languages via sentiment and semantic analysescited by 2
  4. 2025HP-BERT: A framework for longitudinal study of Hinduphobia on social media via language modelscited by 1
  5. 2024Large language model for Bible sentiment analysis: Sermon on the Mountcited by 0
  6. 2026Automated evaluation of LLMs for effective machine translation of Mandarin Chinese to Englishcited by 0