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LREC-COLING 2024main

Linking Judgement Text to Court Hearing Videos: UK Supreme Court as a Case Study

Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)

DOI:10.63317/2rosaaskfbbh

Abstract

One the most important archived legal material in the UK is the video recordings of Supreme Court hearings and their corresponding judgements. The impact of Supreme Court published material extends far beyond the parties involved in any given case as it provides landmark rulings on points of law of the greatest public and constitutional importance. Typically, transcripts of legal hearings are lengthy, making it time-consuming for legal professionals to analyse crucial arguments. This study focuses on summarising the second phase of a collaborative research-industrial project aimed at creating an automatic tool designed to connect sections of written judgements with relevant moments in Supreme Court hearing videos, streamlining access to critical information. Acting as a User-Interface (UI) platform, the tool enhances access to justice by pinpointing significant moments in the videos, aiding in comprehension of the final judgement. We make available the initial dataset of judgement-hearing pairs for legal Information Retrieval research, and elucidate our use of AI generative technology to enhance it. Additionally, we demonstrate how fine-tuning GPT text embeddings to our dataset optimises accuracy for an automated linking system tailored to the legal domain.

Details

Paper ID
lrec2024-main-0927
Pages
pp. 10598-10609
BibKey
saadany-etal-2024-linking
Editor
N/A
Publisher
European Language Resources Association (ELRA) and ICCL
ISSN
2522-2686
ISBN
979-10-95546-34-4
Conference
Joint International Conference on Computational Linguistics, Language Resources and Evaluation
Location
Turin, Italy
Date
20 May 2024 25 May 2024

Authors

  • HS

    Hadeel Saadany

  • CO

    Constantin Orasan

  • SW

    Sophie Walker

  • CB

    Catherine Breslin

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