---
dataset_info:
  features:
  - name: file
    dtype: string
  - name: positive
    dtype:
      audio:
        sampling_rate: 16000
  - name: speaker_id
    dtype: int64
  - name: chapter_id
    dtype: int64
  - name: id
    dtype: string
  - name: anchor
    dtype: string
  splits:
  - name: train
    num_bytes: 23908784883.828
    num_examples: 104014
  - name: validation
    num_bytes: 359846424.966
    num_examples: 2703
  download_size: 23560577435
  dataset_size: 24268631308.794
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
  - split: validation
    path: data/validation-*
pretty_name: BidirLM x Librispeech
---


> ⚠️ **Part of the BidirLM-Omni Collection** > This dataset is a specific modality sub-sample of the corpus used to train the [BidirLM-Omni](https://huggingface.co/BidirLM/BidirLM-Omni-2.5B-Embedding) models. 
> 
> **Looking for the full training mixture?** > If you want to access the complete, balanced 1.8M sample omnimodal dataset (integrating text, image, audio), please visit the global integration hub here:  
> 👉 **[BidirLM/BidirLM-Omni-Contrastive](https://huggingface.co/datasets/BidirLM/BidirLM-Omni-Contrastive)**
---

## 📜 Citation
If you use this processed dataset or the broader BidirLM mixture in your research, please cite our work:

```bibtex
@misc{boizard2026bidirlmtextomnimodalbidirectional,
      title={BidirLM: From Text to Omnimodal Bidirectional Encoders by Adapting and Composing Causal LLMs}, 
      author={Nicolas Boizard and Théo Deschamps-Berger and Hippolyte Gisserot-Boukhlef and Céline Hudelot and Pierre Colombo},
      year={2026},
      eprint={2604.02045},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2604.02045}, 
}
```