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.

翻译：印度法律领域中机器学习（ML）的应用明显不足，且该领域现有的研究通常基于高等法院的英文数据。地方法院及印度各地方语言的数据往往被忽视。本文在印地语法律文档语料库上部署了卷积神经网络（CNN）架构。我们借助CNN模型执行保释预测任务，总体准确率达到93%，较卡普尔等人（2022）基于印度北方邦20个地区数据所设定的基准准确率有所提升。