| | --- |
| | pretty_name: ELR-1000 |
| | license: other |
| | license_name: kpl-by-nc-sa-fs-1.0 |
| | license_link: https://github.com/karya-inc/kpl/blob/main/src/kpl-by-nc-sa-fs.txt |
| | tags: |
| | - recipes |
| | - food |
| | - image |
| | - audio |
| | - text |
| | - multimodal |
| | size_categories: |
| | - 1K<n<10K |
| | citation: | |
| | @inproceedings{joshi2025elr1000, |
| | title = {ELR-1000: A Community-Generated Dataset for Endangered Indic Indigenous Languages}, |
| | author = {Joshi, Neha and Gogoi, Pamir and Mirza, Aasim and Jansari, Aayush and Yadavalli, Aditya and Pandey, Ayushi and Shukla, Arunima and Sudharsan, Deepthi and Bali, Kalika and Seshadri, Vivek}, |
| | booktitle = {Proceedings of the 14th International Joint Conference on Natural Language Processing and the 4th Asia-Pacific Chapter of the Association for Computational Linguistics (IJCNLP-AACL 2025)}, |
| | address = {Mumbai, India}, |
| | month = dec, |
| | year = {2025}, |
| | note = {Preprint: arXiv:2512.01077}, |
| | url = {https://arxiv.org/abs/2512.01077} |
| | } |
| | gated: true |
| | configs: |
| | - config_name: default |
| | data_files: |
| | - split: train |
| | path: "data/*.parquet" |
| | --- |
| | |
| | # ELR-1000: A Community-Generated Dataset for Endangered Indic Indigenous Languages |
| |
|
| | **ELR-1000** is a rich multimodal dataset documenting traditional recipes in 10 endangered and |
| | under-represented languages of India. This community-generated resource contains audio recordings, |
| | images, and text descriptions for 1,073 recipes, preserving culinary knowledge and cultural heritage |
| | through authentic community participation. Our paper documenting the details can be found |
| | [here](https://arxiv.org/abs/2512.01077). |
| |
|
| | ## Dataset Overview |
| |
|
| | This dataset captures the rich culinary traditions of indigenous communities across India, |
| | documenting recipes that have been passed down through generations. Each recipe entry includes: |
| |
|
| | - **Multimodal Content**: Step-by-step images, audio instructions, and detailed text descriptions |
| | - **Cultural Context**: Stories, memories, and cultural significance associated with each dish |
| | - **Practical Information**: Ingredients, tools, storage methods, and dietary considerations |
| | - **Community Voice**: Authentic recordings from community members in their native languages |
| | - **Fair Wages**: All participants were compensated higher-than living wages for their contributions |
| |
|
| | ### Dataset Statistics |
| |
|
| | | Attribute | Value | |
| | | ------------- | --------------------------------------------- | |
| | | Total Recipes | 1,073 | |
| | | Languages | 10 endangered Indic languages | |
| | | Total Images | 11,213 | |
| | | Total Audio | 42 hours | |
| | | Format | Parquet shards (11 files) with embedded media | |
| | | Modalities | Text, Images (JPG), Audio (WAV) | |
| |
|
| | ### Languages Included |
| |
|
| | Assamese, Bodo, Ho, Kaman-Mishmi, Khasi, Khortha, Meitei, Mundari, Sadri, Santhali |
| |
|
| | ## Quick Start |
| |
|
| | ```python |
| | from datasets import load_dataset |
| | import matplotlib.pyplot as plt |
| | import os |
| | import IPython.display as ipd |
| | |
| | # Load dataset |
| | ds = load_dataset("karya/ELR-1000", split="train", token=os.getenv("hf_token")) |
| | sample = ds[0] |
| | |
| | # Display metadata |
| | print(sample['recipe_name'], sample['language'], sample['ingredients']) |
| | |
| | # Display recipe texts |
| | print(sample["recipe_steps_text"]) |
| | |
| | # Display image |
| | if sample['images']: |
| | plt.imshow(sample['images'][0]) |
| | plt.axis('off') |
| | plt.show() |
| | |
| | # Play audio |
| | if sample['user_audio']: |
| | audio = sample['user_audio'][0] |
| | ipd.display(ipd.Audio(data=audio['array'], rate=audio['sampling_rate'])) |
| | ``` |
| |
|
| | ## Dataset Structure |
| |
|
| | The dataset is stored as Parquet files in the `data/` directory. Each Parquet file contains |
| | approximately 100 recipes with embedded media (images and audio stored as bytes within the Parquet |
| | format). |
| |
|
| | ## Data Collection |
| |
|
| | This dataset was created through community participation, with recipes and recordings contributed by |
| | native speakers from various indigenous communities across India. The data collection process |
| | prioritized: |
| |
|
| | - **Authenticity**: Recipes and recordings sourced directly from community members |
| | - **Fair Compensation**: All contributors were paid higher-than-living wages for their participation |
| | - **Informed Consent**: All participants provided explicit consent for their contributions to be shared |
| |
|
| | ## Citation |
| |
|
| | If you use this dataset in your research or projects, please cite the paper: |
| |
|
| | ```bibtex |
| | @inproceedings{joshi2025elr1000, |
| | title = {ELR-1000: A Community-Generated Dataset for Endangered Indic Indigenous Languages}, |
| | author = {Joshi, Neha and Gogoi, Pamir and Mirza, Aasim and Jansari, Aayush and Yadavalli, Aditya and Pandey, Ayushi and Shukla, Arunima and Sudharsan, Deepthi and Bali, Kalika and Seshadri, Vivek}, |
| | booktitle = {Proceedings of the 14th International Joint Conference on Natural Language Processing and the 4th Asia-Pacific Chapter of the Association for Computational Linguistics (IJCNLP-AACL 2025)}, |
| | address = {Mumbai, India}, |
| | month = dec, |
| | year = {2025}, |
| | note = {Preprint: arXiv:2512.01077}, |
| | url = {https://arxiv.org/abs/2512.01077} |
| | } |
| | ``` |
| |
|
| | ## Acknowledgments |
| |
|
| | We gratefully acknowledge the communities and individuals who contributed recipes, recordings, and |
| | cultural knowledge to create this dataset. This work is dedicated to preserving and celebrating the |
| | rich culinary and linguistic heritage of indigenous communities in India. |
| |
|
| | ## License |
| |
|
| | This work is licensed under a [KPL BY-NC-SA-FS 1.0](https://github.com/karya-inc/kpl) license. This |
| | license allows reusers to distribute, remix, adapt, build upon, and incorporate into software |
| | systems, the material in any medium or format for noncommercial purposes only, and only so long as |
| | attribution is given to the creator. If you remix, adapt, build upon, or incorporate into software |
| | systems, you must license the modified material, including material generated by the software |
| | system, under identical terms, and license the software system under the GNU General Public License. |
| |
|
| | ## Commercial Use |
| |
|
| | If you are interested in using this dataset for commercial purposes, please [contact |
| | us](https://www.karya.in/contact/). Profits from commercial licensing will be distributed as |
| | royalties to the community members who contributed to this dataset. |
| |
|
| | ## Contact |
| |
|
| | For questions, issues, or contributions, open an issue on the dataset repository or |
| | [contact us directly](https://www.karya.in/contact/). |
| |
|
