Multilingual Tourist Assistance using ChatGPT: Comparing Capabilities in Hindi, Telugu, and Kannada

Sanjana Kolar, Rohit Kumar
7/28/2023
cs.CL

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Abstract

This research investigates the effectiveness of ChatGPT, an AI language model by OpenAI, in translating English into Hindi, Telugu, and Kannada languages, aimed at assisting tourists in India's linguistically diverse environment. To measure the translation quality, a test set of 50 questions from diverse fields such as general knowledge, food, and travel was used. These were assessed by five volunteers for accuracy and fluency, and the scores were subsequently converted into a BLEU score. The BLEU score evaluates the closeness of a machine-generated translation to a human translation, with a higher score indicating better translation quality. The Hindi translations outperformed others, showcasing superior accuracy and fluency, whereas Telugu translations lagged behind. Human evaluators rated both the accuracy and fluency of translations, offering a comprehensive perspective on the language model's performance.

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Cite this paper

@article{kolar2023multilingual,
  title  = {Multilingual Tourist Assistance using ChatGPT: Comparing Capabilities in Hindi, Telugu, and Kannada},
  author = {Sanjana Kolar and Rohit Kumar},
  year   = {2023},
  eprint = {2307.15376},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2307.15376v1}
}

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