Convolutional Neural Networks can achieve binary bail judgement classification

Amit Barman, Devangan Roy, Debapriya Paul, Indranil Dutta, Shouvik Kumar Guha, Samir Karmakar, Sudip Kumar Naskar

[How to correct problems with metadata yourself]


Abstract
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.
Anthology ID:
2023.icon-1.79
Volume:
Proceedings of the 20th International Conference on Natural Language Processing (ICON)
Month:
December
Year:
2023
Address:
Goa University, Goa, India
Editors:
Jyoti D. Pawar, Sobha Lalitha Devi
Venue:
ICON
SIG:
SIGLEX
Publisher:
NLP Association of India (NLPAI)
Note:
Pages:
773–778
Language:
URL:
https://aclanthology.org/2023.icon-1.79
DOI:
Bibkey:
Cite (ACL):
Amit Barman, Devangan Roy, Debapriya Paul, Indranil Dutta, Shouvik Kumar Guha, Samir Karmakar, and Sudip Kumar Naskar. 2023. Convolutional Neural Networks can achieve binary bail judgement classification. In Proceedings of the 20th International Conference on Natural Language Processing (ICON), pages 773–778, Goa University, Goa, India. NLP Association of India (NLPAI).
Cite (Informal):
Convolutional Neural Networks can achieve binary bail judgement classification (Barman et al., ICON 2023)
Copy Citation:
PDF:
https://preview.aclanthology.org/teach-a-man-to-fish/2023.icon-1.79.pdf