mlsanityData to 7 Oct 2026

LaCour!: Enabling Research on Argumentation in Hearings of the European Court of Human Rights

arXiv 2312.05061 ↗First posted 8 Dec 2023cs.CLcited by 1

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Abstract (arXiv)

Why does an argument end up in the final court decision? Was it deliberated or questioned during the oral hearings? Was there something in the hearings that triggered a particular judge to write a dissenting opinion? Despite the availability of the final judgments of the European Court of Human Rights (ECHR), none of these legal research questions can currently be answered as the ECHR's multilingual oral hearings are not transcribed, structured, or speaker-attributed. We address this fundamental gap by presenting LaCour!, the first corpus of textual oral arguments of the ECHR, consisting of 154 full hearings (2.1 million tokens from over 267 hours of video footage) in English, French, and other court languages, each linked to the corresponding final judgment documents. In addition to the transcribed and partially manually corrected text from the video, we provide sentence-level timestamps and manually annotated role and language labels. We also showcase LaCour! in a set of preliminary experiments that explore the interplay between questions and dissenting opinions. Apart from the use cases in legal NLP, we hope that law students or other interested parties will also use LaCour! as a learning resource, as it is freely available in various formats at https://huggingface.co/datasets/TrustHLT/LaCour.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 17 of its 35 references that are in the map. First posted on arXiv 8 Dec 2023.

Builds on

17 of 35 references.

References · 17

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  2. 2019RoBERTa: A Robustly Optimized BERT Pretraining Approachcited by 13,266
  3. 2019Sentence-BERT: Sentence Embeddings using Siamese BERT-Networkscited by 9,049
  4. 2022Robust Speech Recognition via Large-Scale Weak Supervisioncited by 3,972
  5. 2020wav2vec 2.0: A Framework for Self-Supervised Learning of Speech Representationscited by 3,853
  6. 2023QLoRA: Efficient Finetuning of Quantized LLMscited by 3,355
  7. 2022BERTopic: Neural topic modeling with a class-based TF-IDF procedurecited by 779
  8. 2023LegalBench: A Collaboratively Built Benchmark for Measuring Legal Reasoning in Large Language Modelscited by 328
  9. 2021LexGLUE: A Benchmark Dataset for Legal Language Understanding in Englishcited by 302
  10. 2019Neural Legal Judgment Prediction in Englishcited by 208
  11. 2019pyannote.audio: neural building blocks for speaker diarizationcited by 175
  12. 2022Pile of Law: Learning Responsible Data Filtering from the Law and a 256GB Open-Source Legal Datasetcited by 113
5 more
  1. 2020LEGAL-BERT: The Muppets straight out of Law Schoolcited by 111
  2. 2023LeXFiles and LegalLAMA: Facilitating English Multinational Legal Language Model Developmentcited by 54
  3. 2022Mining Legal Arguments in Court Decisionscited by 35
  4. 2022Legal and Political Stance Detection of SCOTUS Languagecited by 5
  5. 2023A Computational Analysis of Oral Argument in the Supreme Courtcited by 3

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