Data Transcription for India's Supreme Court Documents Using Deep Learning Algorithms

• Published in: International journal of electronic government research Vol. 16; no. 4; pp. 21 - 41
• Main Authors: Vaissnave V, Deepalakshmi, P
• Format: Journal Article
• Language: English
• Published: Hershey IGI Global 01.10.2020
• Subjects: Accuracy; Algorithms; Artificial neural networks; Attorneys; Basketball; Classification; Computerization; Datasets; Deep learning; Documentation; Electronic government; Experiments; Information retrieval; Judiciary; Learning; Legal system; Literature reviews; Litigation; Machine learning; Neural networks; Reasoning; Relevance; Short term memory; Supreme courts; Text categorization
• ISSN: 1548-3886; 1548-3894
• DOI: 10.4018/IJEGR.2020100102

The Indian legal system is one of the largest judiciary systems in the world and handles a huge number of legal cases which is increasing rapidly day by day. The computerized documentation of Indian law is highly voluminous and complex forms. This article proposes a model using deep learning techniques to split the judgment text into the issue, facts, arguments, reasoning, and decision. To evaluate the proposed model, the authors conducted experiments that revealed that the convolutional neural network and long short-term memory transcription technique could achieve better accuracy and obtain superior transcription performance. Comparison results indicate that the proposed algorithm gives the highest classification accuracy rate of 95.6%. The adaptation of splitting the judgment text into the issue, facts, arguments, reasoning, and decision helps to find specific portions of the judgment within a second, making the job of analyzing the case more effective, efficient, and faster.