Datasets:
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---
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}
}
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