Convolutional Neural Networks can achieve binary bail judgement classification
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arXiv
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| Main Authors: | , , , , , , |
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| Format: | Preprint |
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2024
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| _version_ | 1866913209142738944 |
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| author | Barman, Amit Roy, Devangan Paul, Debapriya Dutta, Indranil Guha, Shouvik Kumar Karmakar, Samir Naskar, Sudip Kumar |
| author_facet | Barman, Amit Roy, Devangan Paul, Debapriya Dutta, Indranil Guha, Shouvik Kumar Karmakar, Samir Naskar, Sudip Kumar |
| contents | There is an evident lack of implementation of Machine Learning (ML) in the legal domain in India, and any research that does take place in this domain is usually based on data from the higher courts of law and works with English data. The lower courts and data from the different regional languages of India are often overlooked. In this paper, we deploy a Convolutional Neural Network (CNN) architecture on a corpus of Hindi legal documents. We perform a bail Prediction task with the help of a CNN model and achieve an overall accuracy of 93\% which is an improvement on the benchmark accuracy, set by Kapoor et al. (2022), albeit in data from 20 districts of the Indian state of Uttar Pradesh. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2401_14135 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Convolutional Neural Networks can achieve binary bail judgement classification Barman, Amit Roy, Devangan Paul, Debapriya Dutta, Indranil Guha, Shouvik Kumar Karmakar, Samir Naskar, Sudip Kumar Computation and Language Computers and Society Machine Learning There is an evident lack of implementation of Machine Learning (ML) in the legal domain in India, and any research that does take place in this domain is usually based on data from the higher courts of law and works with English data. The lower courts and data from the different regional languages of India are often overlooked. In this paper, we deploy a Convolutional Neural Network (CNN) architecture on a corpus of Hindi legal documents. We perform a bail Prediction task with the help of a CNN model and achieve an overall accuracy of 93\% which is an improvement on the benchmark accuracy, set by Kapoor et al. (2022), albeit in data from 20 districts of the Indian state of Uttar Pradesh. |
| title | Convolutional Neural Networks can achieve binary bail judgement classification |
| topic | Computation and Language Computers and Society Machine Learning |
| url | https://arxiv.org/abs/2401.14135 |