Papers by Dhrubajyoti Pathak
Evaluating Performance of Pre-trained Word Embeddings on Assamese, a Low-resource Language (2024.lrec-main)
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| Challenge: | Word embeddings are not explored in high-resource languages such as Assamese, where resources are limited. |
| Approach: | They propose to use assamese pre-trained word embeddings for sequence labeling tasks such as Parts-of-speech and Named Entity Recognition to evaluate their performance. |
| Outcome: | The proposed embeddings outperform the existing methods on Parts-of-speech and Named Entity Recognition tasks. |
AsNER - Annotated Dataset and Baseline for Assamese Named Entity recognition (2022.lrec-1)
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| Challenge: | Named entity recognition (NER) is a type of annotation that classifies text into predefined classes such as person, location, organization etc. |
| Approach: | They propose to use a named entity annotation dataset for low resource Assamese language with a baseline NER model. |
| Outcome: | The proposed dataset is likely to be significant resource for deep neural based Assamese language processing. |