Update README.md

README.md

@@ -1,3 +1,136 @@
----
-license: pddl
----
+---
+datasets:
+- freococo/rohingya_asr_audio
+language:
+- rhg
+tags:
+- speech
+- audio
+- voa
+- rohingya
+- self-supervised
+- webdataset
+- public-domain
+pretty_name: VOA Rohingya ASR
+license: pddl
+task_categories:
+- automatic-speech-recognition
+- audio-to-audio
+- audio-classification
+language_creators:
+  - found
+source_datasets:
+  - original
+---
+
+## Overview
+
+This dataset contains broadcast audio recordings from the **Voice of America (VOA) Rohingya Service**. Each file represents a daily news segment, typically 30 minutes in length, automatically segmented into chunks of 5–15 seconds for use in **self-supervised ASR**, **pretraining**, **language identification**, and more.
+
+The content was aired publicly as part of VOA’s Rohingya-language radio program and is therefore released under a **public domain dedication** (U.S. Government speech, [17 U.S.C. § 105](https://www.govinfo.gov/content/pkg/USCODE-2011-title17/html/USCODE-2011-title17-chap1-sec105.htm)).
+
+The dataset is stored in **WebDataset format**, with each `.tar` archive containing paired `.audio` (MP3) and `.json` metadata files for each segment.
+
+## Acknowledgments
+
+This dataset would not exist without the dedication and professionalism of the **Voice of America Rohingya Service** — especially the **journalists, editors, producers, and engineers** who continue broadcasting trusted news and public service content to marginalized communities.
+
+Special gratitude goes to:
+
+- VOA multilingual teams who **created, edited, and voiced** this content
+- The **American people**, whose hard-earned taxpayer contributions make public media like VOA possible
+- The open-source, low-resource, and humanitarian tech community — for tools, models, and continued support
+
+This dataset is released in the hope that it will:
+- Advance multilingual speech technology
+- Empower access to information
+- Amplify underrepresented voices across the world
+
+## Metrics
+
+| Metric            | Value        |
+|-------------------|--------------|
+| Total audio hours | **357.55 h** |
+| Audio chunks      | **131,860**  |
+| Shard count       | **14**       |
+| Average chunk size| 6–15 sec     |
+| Format            | WebDataset   |
+| License           | Public Domain (VOA / U.S. Gov) |
+
+## Quick-start
+
+You can load and stream the dataset from Hugging Face using the `datasets` library:
+
+    from datasets import load_dataset
+
+    dataset = load_dataset(
+        "freococo/rohingya_asr_audio",
+        split="train",
+        streaming=True
+    )
+
+    for sample in dataset:
+        print(sample["audio"])           # Audio object
+        print(sample["file_name"])       # Chunk file name
+        print(sample["download_url"])    # Original source URL
+        print(sample["duration"])        # Duration in seconds
+
+## Known Limitations
+
+This dataset was created through automatic chunking of full-length VOA Rohingya news broadcasts. As a result, developers should be aware of the following limitations:
+
+- **No transcriptions** are included. This dataset is not aligned for supervised training unless transcribed independently.
+- Some chunks may contain **non-speech segments** such as:
+    - Music intros and outros
+    - Jingles or filler transitions
+    - Background crowd noise or environmental sounds
+    - Silent or low-audio intervals
+- **No speaker labeling** is provided. Voice diversity, accents, and gender variation exist, but are unlabeled.
+- **Broadcast mixing artifacts** may affect ASR performance in noisy conditions (e.g., overlayed music, crossfades, background hum).
+
+Despite these challenges, the dataset is suitable for:
+- Pretraining ASR models (wav2vec2-style)
+- Unsupervised learning
+- Language ID and diarization
+- Synthetic data generation
+
+We recommend applying **speech detection filters**, **VAD**, or **manual quality control** for downstream supervised tasks.
+
+## Dataset Details
+
+Each training sample is stored as:
+
+- `.audio` — MP3 audio content (~5–15 seconds)
+- `.json` — metadata with:
+
+    - `file_name`: full chunk filename (e.g., `20250310_0001.audio`)
+    - `original_file`: e.g., `20250310`
+    - `publish_date`: ISO 8601 format (e.g., `2025-03-10`)
+    - `download_url`: original VOA source URL
+    - `duration`: chunk duration in seconds
+
+These files are stored in `.tar` archives, split into ~10,000-sample shards named like:
+
+    rohingya-00000.tar
+    rohingya-00001.tar
+    ...
+
+Each archive follows [WebDataset format](https://github.com/webdataset/webdataset), making it easy to use with PyTorch and Hugging Face streaming.
+
+## License & Reuse
+
+All content is in the **public domain** under U.S. law:
+
+> U.S. Government speech recordings (VOA staff broadcasts) are public domain under [17 U.S.C. § 105](https://www.govinfo.gov/content/pkg/USCODE-2011-title17/html/USCODE-2011-title17-chap1-sec105.htm).
+
+Some broadcasts may contain music or third-party clips. Please verify manually if using for commercial purposes.
+
+## Citation
+
+If you use this dataset in research, please cite:
+
+> **Freococo (2025).**  
+> *VOA Rohingya ASR*  
+> Hugging Face: [https://huggingface.co/datasets/freococo/rohingya_asr_audio](https://huggingface.co/datasets/freococo/rohingya_asr_audio)  
+> Public-domain speech segments from VOA Rohingya news programming.  
+> Released under `pddl`.