Chittaranjan Swain
2025
Development of a Low-Cost Named Entity Recognition System for Odia Language using Deep Active Learning
Tusarkanta Dalai
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Tapas Kumar Mishra
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Pankaj Kumar Sa
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Prithviraj Mohanty
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Chittaranjan Swain
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Ajit Kumar Nayak
Proceedings of the Workshop on Beyond English: Natural Language Processing for all Languages in an Era of Large Language Models
Spatio-Temporal Mechanism in Multilingual Sentiment Analysis
Adarsh Singh Jadon
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Vivek Tiwari
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Chittaranjan Swain
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Deepak Kumar Dewangan
Proceedings of the Workshop on Beyond English: Natural Language Processing for all Languages in an Era of Large Language Models
This study investigated the effectiveness of various models in deep learning in performing sentiment analysis on code-mixed Hinglish text, a hybrid language is widely used in digital telecommunication. Hinglish presents unique challenges due to its informal nature, frequent code-switching, and complex linguistic structure. This research leverages datasets from the HinGE, SemEval-2020 Task 9 & E-Commerce Reviews, datasets, competition, and employ models such as RNN (LSTM), BERT-LSTM, CNN, and a proposed BiLSTM model with Data Augmentation.