README.md

metadata

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

This is the first public Rohingya language ASR dataset in AI history.

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).

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, 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.

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
Public-domain speech segments from VOA Rohingya news programming.
Released under pddl.