---
license: mit
task_categories:
- audio-to-audio
language:
- en
---

# Libri Conversation FLAC Dataset

This dataset accompanies the paper:

**[Proactive Hearing Assistants that Isolate Egocentric Conversations](https://www.arxiv.org/abs/2511.11473)**  
*Hu et al., 2025*

It contains **~234 hours of conversational-style audio** derived from LibriSpeech-like sources, processed into 60-second multispeaker segments under different experimental conditions:

- **libri_leaving** — scenarios where one speaker intermittently leaves the conversation  
- **libri_multi** — 3-speaker conversational segments

All audio is stored in **FLAC** format. Metadata files (JSON) are preserved exactly as in the original directory structure.

---

## Dataset Structure

The dataset is organized into two main components:

    libri_leaving/
      train/
      val/
      test/

    libri_multi/
      train/
      val/
      test/

Because of Hugging Face API request limits, the dataset is packaged into `.tar` archives.  
Each archive mirrors the original folder structure:

    libri_leaving_train.tar
    libri_leaving_val.tar
    libri_leaving_test.tar

    libri_multi_train.tar
    libri_multi_val.tar
    libri_multi_test.tar

---

## Citation

If you use this dataset, please cite the following paper:

    @inproceedings{hu2025proactive,
      title={Proactive Hearing Assistants that Isolate Egocentric Conversations},
      author={Hu, Guilin and Itani, Malek and Chen, Tuochao and Gollakota, Shyamnath},
      booktitle={Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing},
      pages={25377--25394},
      year={2025}
    }