| --- |
| license: odc-by |
| --- |
| OLMoASR-Mix is the curated version of OLMoASR-Pool, a web-scale audio-text dataset collected from the public internet. The dataset consists of approximately 1M hours of audio. |
|
|
| With OLMoASR-Mix from OLMoASR-Pool, we trained OLMoASR 💬🎙️, a series of English speech recognition models and observed strong generalization and robust capabilities! |
|
|
| # Content |
| The dataset spans approximately 1M hours of audio. |
| It also spans across a variety speaking styles, accents and audio setups such as news segments 📰, podcasts 🎙️, outdoors 🌳🏙️, crowds 🧑🤝🧑, speeches 🎤, commentary 🗣️, interviews 🤳 and more! |
| OLMoASR-Mix is English-only as it has been curated for training English speech recognition models. |
|
|
| # Usage |
| Download from HuggingFace |
| Retrieve HF access token from here to gain access to the dataset. |
| Run pip install huggingface_hub[cli] |
| Run huggingface-cli login in your CLI and paste the HF access token to login |
| Use the code below to access the IDs |
| ``` |
| from datasets import load_dataset |
| dataset = load_dataset("allenai/OLMoASR-Mix", streaming=True) |
| print(dataset) # features: ['id'] |
| print(next(iter(dataset['train']))) |
| ``` |
| If you're downloading all the IDs, you can run the code below |
| ``` |
| from datasets import load_dataset |
| dataset = load_dataset("allenai/OLMoASR-Mix", streaming=False, cache_dir=<where you want to download the IDs to>) |
| ``` |
| Download the audio and transcript files from ID information. |
| Preprocess the audio and transcript files. Follow the instructions at the OLMoASR repo. |
| |
| # Uses |
| The collection was used to train a speech recognition model, but it can also be used in research areas such as conversational data, audio understanding, speaker diarization, voice detection and more. |
| |
| # License |
| This dataset is licensed under ODC-BY. It is intended for research and educational use in accordance with Ai2's Responsible Use Guidelines. |
| |
| # Reference |
| ``` |
| @misc{ngo2025olmoasropenmodelsdata, |
| title={OLMoASR: Open Models and Data for Training Robust Speech Recognition Models}, |
| author={Huong Ngo and Matt Deitke and Martijn Bartelds and Sarah Pratt and Josh Gardner and Matt Jordan and Ludwig Schmidt}, |
| year={2025}, |
| eprint={2508.20869}, |
| archivePrefix={arXiv}, |
| primaryClass={cs.SD}, |
| url={https://arxiv.org/abs/2508.20869}, |
| } |
| ``` |
| # Contact |
| If you have any questions regarding the dataset, please contact Huong Ngo at zoengo2002@gmail.com. |
