Re: sanskrit SENTIMENT Analysis-iitR...

[विश्वासो वासुकिजः (Vishvas Vasuki)]

Thanks! Please just email + sanskrit-programmers stream henceforth for wider reach.

On Fri, 23 Sept 2022 at 11:49, Gagan Mandayam <gagan.m...@gmail.com> wrote:

Dear Sri Vishvas,

any good Sanskrit Article /Research articles are shared;

-- ie  23.9.22- IIT Roorkee researchers develop sentiment analysis method for Sanskrit texts- Agrima Srivastava

The model has been published as a research paper in the journal, ‘Applied Intelligence’. (Express Photo)

Researchers at the Indian Institute of Technology, Roorkee have developed an efficient method for Sanskrit text sentiment analysis.
The proposed technique has achieved 87.50 per cent accuracy for machine translation and 92.83 per cent accuracy for sentiment classification.

These methods were not explored to its full potential, because of the unavailability of sufficient labeled data.
The research proposed a method that comprises models for machine translation, translation evaluation, and sentiment analysis.

The machine translations have been used as cross-lingual mapping of the source and the target language.
The obtained English translations are sufficiently mature and natural as the original English sentences.

The dataset to perform this research was taken from the Valmiki Ramayana website which has been developed and maintained by the researchers of IIT Kanpur.
The researchers plan to explore the morphological properties of Sanskrit, for better classification using only root words and their respective suffixes and prefixes.

They are also planning to evaluate whether the morphological richness of Sanskrit, is retained while translating it to English.
And, they also plan to obtain a model that discerns the context of words in multiple languages and provides word embeddings of lesser dimensions.
The model has been published as a research paper in the journal, ‘Applied Intelligence’.



--- http://bweducation.businessworld.in/article/Researchers-Develop-Classification-Method-For-Sanskrit-Text/22-09-2022-447776/

23.9.22--Researchers Develop Classification Method For Sanskrit Text
IIT Roorkee researchers develop a sentiments analysis method for Sanskrit text that has achieved 92.83 per cent accuracy for sentiment classification in Sanskrit text

Sanskrit is one of the world’s most ancient languages; however, natural language processing tasks such as machine translation and sentiment analysis have not been explored.
Indian Institute of Technology Roorkee (IIT Roorkee) researchers have developed an efficient method for Sanskrit text sentiment analysis.
The proposed technique has achieved 87.50 per cent accuracy for machine translation and 92.83 per cent accuracy for sentiment classification.

The research proposed a method that comprises models for machine translation, translation evaluation, and sentiment analysis.
The team involved in this research are Prof. Balasubramanian Raman, Department of Computer Science and Engineering and his PhD student Puneet Kumar, and M.Sc. student Kshitij Pathania, Department of Mathematics.

The machine translations have been used as cross-lingual mapping of the source and the target language.
The obtained English translations are sufficiently mature and natural as the original English sentences.
The model has been published as a Research Paper in a reputed peer-reviewed journal Applied Intelligence;

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springer 2022 sanskrit sentiment analysis

Puneet Kumar, Kshitij Pathania and Balasubramanian Raman, Zero-shot learning based crosslingual sentiment analysis for Sanskrit text with insufficient labeled data;
Accepted for publication in Applied Intelligence (Springer), 2022.

--- https://github.com/MIntelligence-Group/SanskritTSA

Code Files
The code files are currently private as the corresponding research paper in Springer Applied Intelligence Journal is under review.
They will be made publically available soon after the paper is published/accepted for publication.

Dataset Access
Access to the ‘IIT-R STSA (IIT-R Sanskrit Text Sentiment Analysis) dataset’ can be obtained by through 'Access Form - IIT-R TIER Dataset.pdf'. The dataset is compiled by Puneet Kumar and Kshitij Pathania at Machine Intelligence Lab, IIT Roorkee under the supervision of Prof. Balasubramanian Raman. It contains 12,892 Sanskrit Sentences, their corresponding English Translations and Sentiment Scores between 0 and 1 (where 0 denotes negative sentiment and 1 denotes positive sentiment).

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--Dhanyosmi Gagan Mandayam- 0-994-524-4397

Spirituality MetaData Analyst; SRI- 'SriVaishnavism Repository Initiative'

-15/106, 11th 'a' cross, 11th Main, Malleswaram, Bangalore-560003.

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Vishvas /विश्वासः