---
license: cc0-1.0
pretty_name: MRTV Voices
language:
  - my
tags:
  - speech
  - audio
  - asr
  - myanmar
  - burmese
  - cc0
  - webdataset
  - government-media
  - mrtv
task_categories:
  - automatic-speech-recognition
  - audio-classification
size_categories:
  - 100K<n<1M
dataset_info:
  total_duration: "116 hours 56 minutes"
  chunk_count: 130782
  shard_count: 1
  format: WebDataset (.tar.gz)
---
## 🗣️ Overview

**MRTV Voices** is a large-scale Burmese speech dataset built from publicly available news broadcasts and programs aired on **Myanma Radio and Television (MRTV)** — the official state-run media channel of Myanmar.

> 🎙️ It contains over **130,000 short audio clips** (≈117 hours) with **aligned transcripts** derived from auto-generated subtitles.

This dataset captures:

- **Formal Burmese** used in government bulletins and official reports  
- **Clear pronunciation**, enunciation, and pacing — ideal for ASR training  
- Diverse speech contexts: *news reading, field reporting, interviews, and announcements*

Whether you're working on:

- **Automatic Speech Recognition (ASR)**  
- **Language model fine-tuning**  
- **Media analysis**  
- or **Myanmar speech research**

...**MRTV Voices** offers one of the most structured and scalable resources for developing Burmese AI systems.

## 📂 Dataset Structure

This dataset is packaged as a single `.tar.gz` archive (`mrtv_voices_000001.tar.gz`) using the **WebDataset format**, which is optimized for high-throughput streaming and model training.

Each audio-text pair includes:

- 🎧 `.mp3` — a short audio chunk (typically 1–6 seconds)
- 📄 `.json` — a rich metadata file containing the transcript and contextual info

All files are named using random UUIDs (e.g., `d84f1e09f1ab4a79.mp3`), and grouped flatly inside the archive.

### 📦 Inside each `.json` file:

| Field            | Description |
|------------------|-------------|
| `file_name`      | Chunk filename (e.g., `abc123.mp3`) |
| `original_file`  | The original MRTV video filename |
| `transcript`     | Subtitle text in Burmese |
| `duration`       | Audio duration (in seconds) |
| `video_url`      | Link to original video |
| `language`       | Always `"my"` (Myanmar) |
| `title`          | Title of the broadcast or clip |
| `description`    | Additional context or social caption |
| `view_count`     | Views at the time of scraping |
| `like_count`     | Likes at the time of scraping |
| `comment_count`  | Comment count |
| `repost_count`   | Repost/share count |
| `channel`        | Channel name (e.g., `MRTV`) |
| `upload_date`    | Date in `YYYYMMDD` format |
| `hashtags`       | List of hashtags (if any) |
| `thumbnail`      | Thumbnail image URL |
| `source`         | Always: `Myanma Radio and Television`

---

The dataset can be loaded using:

- 🤗 **Hugging Face Datasets** (`load_dataset(..., streaming=True)`)
- 🧠 **WebDataset** for PyTorch
- Custom Python scripts

## 🚀 How to Use

You can stream this dataset directly using 🤗 `datasets`. Each sample contains both the transcript and full metadata.

```python
from datasets import load_dataset

# The library automatically finds the .tar.gz shard in the repo
ds = load_dataset(
    "freococo/mrtv_news_voices",
    split="train",
    streaming=True
)

# Iterate through the first 5 samples
for sample in ds.take(5):
    # The transcript is a top-level feature for easy access
    print(f"🎙️ Transcript: {sample['txt']}")

    # The audio data is in the 'mp3' column
    audio_data = sample['mp3']
    audio_array = audio_data['array']
    sampling_rate = audio_data['sampling_rate']
    print(f"🎧 Audio loaded with shape {audio_array.shape} and rate {sampling_rate} Hz")

    # The 'json' column is ALREADY a Python dictionary
    metadata = sample['json']
    print(f"📺 Channel: {metadata.get('channel')}")
    print(f"🎥 Video URL: {metadata.get('video_url')}")
    print("---")
```
## ⚠️ Limitations

While this dataset offers broad coverage of Burmese speech and media clips, it is important to understand its limitations:

- **Propagandistic content**: MRTV is a state-run broadcaster currently operated by the military regime. Some content may contain nationalist, anti-democracy, anti-Western, or racially biased perspectives.
- **Zero human correction**: All transcriptions were scraped directly from TikTok auto-captions, with **no manual editing**. Around 25–35% may contain spelling errors, punctuation artifacts, or missing words.
- **Censorship bias**: Editorial control by the regime means some topics (e.g. dissent, protest) are absent or misrepresented.
- **Speaker diversity**: Most clips are from formal news or PR settings. Street speech, dialects, and youth slang are underrepresented.
- **ASR challenges**: Some captions have poor alignment or are missegmented, which could affect training quality unless filtered or fine-tuned.

---

### ✅ Why It’s Still Useful

Despite the caveats:

> Even if you discarded every noisy sample, you’d still have over **100,000 high-quality Burmese audio-text pairs** — suitable for ASR training, forced alignment, or language model pretraining.

This is one of the **largest open Burmese speech datasets ever released** — with real voices, real pronunciation, and full metadata.

Use with care. Filter where needed. And always document your preprocessing steps when publishing derived models.

## 📜 License and Intent

This dataset is released under the **Universal Public Domain Dedication (CC0 1.0 Universal)** license.

All content was collected from the publicly accessible **state-owned Myanmar Radio and Television (MRTV)** channel on TikTok.

---

### ⚠️ Important Context

- MRTV is currently operated by the Myanmar military regime.
- Videos were produced using public funds, state media resources, and government-owned facilities.
- As such, the **content belongs to the people of Myanmar** — and should be available for open use, research, and analysis.

---

### ✅ You May:

- Use, modify, and redistribute this dataset.
- Train **open-source** or **commercial AI models**.
- Build tools that help **preserve the Burmese language**.
- Analyze, audit, or critique the media for public accountability.

---

### ❌ You May NOT:

- Misrepresent the source of the data.
- Use the voices or transcriptions to impersonate real people or endorse ideologies.
- Claim ownership of the original MRTV media content.

---

This dataset is shared **in the public interest**, for language accessibility, open research, and education.

It does **not endorse** any specific political regime, message, or actor.

> Use responsibly, document your pipeline, and help make Burmese speech technology accessible to all.

## 💬 Author’s Note

This dataset was compiled, cleaned, and published by **freococo**, a Myanmar-born open-source advocate and AI researcher.

I receive **no financial compensation** for this work.

I built this dataset because:

- 🧠 Burmese (Myanmar) is still underrepresented in speech and language technology.
- 📣 Our voices deserve to be part of global AI — not left behind.
- 🕊️ Language preservation is resistance against cultural erasure.

---

> MRTV is a controversial source — I understand that. ***But speech is speech.***  
And if we're training machines to listen, **they must hear everyone**.

This dataset includes laughter, announcements, news delivery, monologues, interviews, and everyday public speech from Myanmar.

Even if it's imperfect or biased — it’s real.  
It reflects **how Burmese is spoken in state media**, with clear pronunciation, varied cadence, and diverse speaker profiles.

Use this to build tools, evaluate speech systems, or simply understand how Burmese sounds in a formal media setting.

> ***This is not just about data — it’s about visibility, dignity, and linguistic equality.***

🫡🇲🇲

## 📚 Citation

```bibtex
@misc{freococo2025mrtvvoices,
  title        = {MRTV Voices: A Burmese Speech Dataset from State Broadcasts},
  author       = {freococo},
  year         = {2025},
  howpublished = {Hugging Face Datasets},
  url          = {https://huggingface.co/datasets/freococo/mrtv_voices}
}