Semantic and Sentiment Analysis of Selected Bhagavad Gita Translations Using BERT-Based Language Framework
نویسندگان
چکیده
It is well known that translations of songs and poems not only break rhythm rhyming patterns, but can also result in loss semantic information. The Bhagavad Gita an ancient Hindu philosophical text originally written Sanskrit features a conversation between Lord Krishna Arjuna prior to the Mahabharata war. one key sacred texts Hinduism as forefront Vedic corpus Hinduism. In last two centuries, there has been lot interest philosophy from western scholars; hence, translated number languages. However, much work validates quality English translations. Recent progress language models powered by deep learning enabled better understanding with sentiment analysis. Our motivated recent methods. this paper, we present framework compares selected (from English) using analyses. We use hand-labelled dataset for tuning state-of-art learning-based model bidirectional encoder representations transformers (BERT). provide analysis chapters verses across results show although style vocabulary respective vary widely, similarity shows message conveyed are mostly similar.
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ژورنال
عنوان ژورنال: IEEE Access
سال: 2022
ISSN: ['2169-3536']
DOI: https://doi.org/10.1109/access.2022.3152266