| --- |
| license: cc0-1.0 |
| language: |
| - zom |
| pretty_name: Zomi ASR |
| tags: |
| - automatic-speech-recognition |
| - audio |
| - zomi |
| - kuki-chin |
| - burmese |
| - myanmar |
| - webdataset |
| - public-domain |
| task_categories: |
| - automatic-speech-recognition |
| - audio-to-audio |
| - audio-classification |
| language_creators: |
| - found |
| source_datasets: |
| - original |
| --- |
| **This is the first public Zomi language ASR dataset in AI history.** |
|
|
| # Zomi ASR |
|
|
| This dataset contains audio recordings and aligned metadata in the **Zomi** language — a collective ethnolinguistic identity adopted by some Kuki-Chin language-speaking communities in Myanmar and India. The term **Zomi** means "Zo people", derived from the root word **Zo** (ancestral identity) and **mi** meaning "people." While originally coined to encompass all Zo-related communities, usage of the term varies regionally and politically. |
|
|
| All audio segments in this dataset were sourced from publicly available news broadcasts by **Zoland Voice TV**, an ethnic-language news channel affiliated with the **National Unity Government (NUG)** of Myanmar. These broadcasts promote information access in minority languages, including Zomi. |
|
|
| The dataset includes over **18.99 hours** of segmented and labeled audio, prepared in [WebDataset](https://github.com/webdataset/webdataset) format, with paired `.audio` and `.json` files suitable for training automatic speech recognition (ASR) systems. |
|
|
| ### Acknowledgments |
|
|
| Special thanks to: |
|
|
| - **Zoland Voice TV and PVTV** for producing and releasing multilingual content freely |
| - **National Unity Government (NUG)** for supporting inclusive language outreach |
| - Volunteers and researchers advancing low-resource ASR for ethnic languages |
|
|
| ## Dataset Structure & Format |
|
|
| This dataset follows the [WebDataset](https://github.com/webdataset/webdataset) format. Each training sample consists of two paired files inside a tar archive: |
|
|
| - `XXXX.audio` — the audio chunk (in MP3 format) |
| - `XXXX.json` — the corresponding metadata (UTF-8 JSON) |
|
|
| 🟢 Minimum chunk duration: 2.04 sec |
| 🔴 Maximum chunk duration: 15.05 sec |
|
|
| Each `.json` file contains the following fields: |
|
|
| ```json |
| { |
| "file_name": "XXXX.audio", |
| "video_id": "YouTubeVideoID", |
| "title": "Original broadcast title from Zoland Voice TV", |
| "url": "https://www.youtube.com/watch?v=YouTubeVideoID", |
| "duration": 13.24 |
| } |
| ``` |
| ## Usage Example |
|
|
| You can load and stream this dataset using the Hugging Face `datasets` library: |
| ``` |
| from datasets import load_dataset |
| |
| dataset = load_dataset( |
| "freococo/zomi_asr", |
| split="train", |
| streaming=True |
| ) |
| |
| for sample in dataset: |
| print(sample["audio"]) # Audio object |
| print(sample["file_name"]) # Chunk filename |
| print(sample["duration"]) # Duration in seconds |
| print(sample["title"]) # Broadcast title |
| print(sample["url"]) # YouTube source URL |
| ``` |
| Each sample includes: |
| - `audio`: the audio chunk (stored as `.audio`, typically MP3 format) |
| - `file_name`: filename of the chunk |
| - `title`: broadcast title in Zomi or Burmese |
| - `url`: original YouTube video link |
| - `video_id`: YouTube video ID |
| - `duration`: duration of the audio in seconds |
|
|
| ## Known Limitations |
|
|
| This dataset was segmented automatically from broadcast videos using pause-based or fixed-length chunking. As such: |
|
|
| - **No transcriptions** are included. |
| - Some chunks may contain **background music**, **news jingles**, or **non-speech segments**. |
| - No **speaker labels**, **noise filtering**, or **speech-vs-music tagging** is applied. |
| - Audio quality varies depending on the original broadcast conditions. |
|
|
| Despite these limitations, this dataset is the most comprehensive public resource available for developing ASR and pretraining models in the Zomi language. |
|
|
| ## Licensing & Use |
|
|
| All content is released under the **Creative Commons Zero (CC0 1.0 Universal)** public domain dedication. |
|
|
| You are free to: |
| ``` |
| - Use, adapt, and remix the data |
| - Train both open and commercial models |
| - Publish derivative works, applications, and papers |
| ``` |
| We ask users to respect the dignity and intent of the original community broadcasts. |
|
|
| ## 📚 Citation |
|
|
| > **Freococo (2025).** |
| > *Zomi ASR* |
| > [https://huggingface.co/datasets/freococo/zomi_asr](https://huggingface.co/datasets/freococo/zomi_asr) |
| > Dataset compiled from Zoland Voice TV ethnic news broadcasts in the Zomi language. |
| > Released under CC0 1.0 (Public Domain). |
