README.md

---
license: other
license_name: custom
license_link: LICENSE
pretty_name: Media Queen Entertainment Voices
language:
  - my
tags:
  - audio
  - speech-recognition
  - asr
  - myanmar
  - burmese
  - low-resource
  - fair-use
  - tiktok
  - webdataset
task_categories:
  - automatic-speech-recognition
  - audio-classification
---

# Media Queen Entertainment Voices

> Where the stars speak, and their stories come to life.

**Media Queen Entertainment Voices** is a massive, large-scale collection of **190,013 short audio segments** (totaling approximately **125 hours** of speech) derived from public videos by **Media Queen Entertainment** — a prominent digital media channel in Myanmar focused on celebrity news, lifestyle content, and in-depth interviews.

The source channel regularly features:
- Interviews with artists, actors, creators, and public figures.
- Behind-the-scenes content and event coverage.
- Authentic, conversational discussions on culture and entertainment.

These videos capture the natural, everyday voices of Myanmar's vibrant cultural scene, making this dataset an invaluable resource for building robust, real-world speech technology.

---

### ❤️ Why I Built This

- Myanmar (Burmese) is often labeled a “low-resource language” in the AI world.
- I don’t reject that label because it’s false — I reject it because it reflects global neglect.
- I built this dataset to show what’s possible — to give Myanmar speech the visibility, respect, and technical foundation it deserves.

I care about languages. I care about people being heard.
And if AI is going to learn from voices — I want it to hear mine, ours, Myanmar’s.

> If you want your voice to be heard — you must first teach the machines to listen.

---

### 🕊️ Why It Matters to Me

We will come, and we will go.
But if your voice is integrated into AI technology — it will go on. Forever.

I cannot build you a pyramid like the ancient Egyptians did.
But I can build something more accessible, more global:
A living archive — of your beautiful, strong, and clear voices.

Maybe, just maybe — AI will speak our beautiful Myanmar language through your voice.
And I believe it will.
I truly do. 🙂

---

### 🔍 What's Included

- **`190,013`** audio-text chunks
- **`~125 hours`** of real Burmese speech (125h 15m 23s)
- Auto-transcribed captions with timestamps
- Rich video metadata (title, views, likes, hashtags)
- A collection of **20** WebDataset-ready `.tar.gz` shards for efficient streaming & training

## 📂 Dataset Structure

This dataset is packaged as **20 sharded `.tar.gz` archives** containing paired audio, transcript, and metadata files in the WebDataset format.

Each sample consists of three files, grouped by a unique key:
- `.mp3` — a short audio chunk extracted from a video.
- `.txt` — the aligned transcript for the audio chunk.
- `.json` — rich metadata including the source video context.

All files are named using UUIDs:
```
a3f1d9e671a44b88.mp3
a3f1d9e671a44b88.txt
a3f1d9e671a44b88.json
```
The `.json` file contains the following fields:

| Field           | Description |
|----------------|-------------|
| `file_name`     | Name of the chunked audio file |
| `original_file` | Source video’s `.mp3` filename |
| `transcript`    | Burmese caption (also in the separate .txt file) |
| `duration`      | Duration of the chunk (in seconds) |
| `video_url`     | Link to the original source video |
| `language`      | Always `"my"` (Myanmar) |
| `title`         | Title of the video |
| `description`   | Full video description |
| `view_count`    | View count at the time of download |
| `like_count`    | Like count |
| `channel`       | Publisher name and description |
| `upload_date`   | In `YYYYMMDD` format |
| `hashtags`      | List of hashtags from the description |
| `thumbnail`     | URL to video thumbnail |
| `source`        | URL to the source TikTok channel |

---

## 🚀 How to Use

This dataset is designed for modern, large-scale training pipelines and is compatible with 🤗 Hugging Face Datasets.

### ✅ Load using Hugging Face Datasets (streaming)

This is the recommended way to use the dataset, as it avoids downloading all ~5.7 GB at once.

```python
from datasets import load_dataset
import json

# The library automatically finds all .tar.gz shards
ds = load_dataset(
    "freococo/media_queen_entertaiment_voices",
    split="train",
    streaming=True
)

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

    # The audio can be accessed directly as a NumPy array
    audio_array = sample['audio']['array']
    sampling_rate = sample['audio']['sampling_rate']
    print(f"🎧 Audio loaded with shape {audio_array.shape} and rate {sampling_rate} Hz")

    # The full metadata is still available in the JSON string
    metadata = json.loads(sample['json'])
    print(f"📺 Channel: {metadata.get('channel')}")
    print(f"🎥 Video URL: {metadata.get('video_url')}")
    print("---")
```

## 🙏 Special Thanks

This dataset would not exist without the incredible creative and production efforts of:

- 🌟 **Media Queen Entertainment** and its entire team.
- 🎤 The journalists, hosts, and interviewers who guide the conversations.
- 🗣️ The artists, creators, and public figures who generously shared their stories and perspectives.
- 🎥 The producers, editors, and behind-the-scenes teams who bring these moments to light.

These individuals are not just content creators — they are curators of culture. Their work provides a vibrant, authentic window into the heart of Myanmar's entertainment world.

---

> Thank you for giving us your voices.
> Now, they may echo in the machines we build — not to replace you,
> but to **remember you**.

🫡🇲🇲🧠📣

## ⚠️ Limitations

While this dataset offers unprecedented scale for Burmese speech, it is not without imperfections.

- **Auto-caption errors**: All transcripts were generated by an automated system (Whisper). A portion of segments may contain minor to moderate transcription errors.
- **No human corrections**: No post-processing or human-in-the-loop editing was performed. This dataset reflects the raw, real-world performance of an automated pipeline.
- **Audio quality**: While generally clear, some clips may include background noise, music overlays, or sound effects common in entertainment media.
- **Representational Focus**: The dataset primarily features voices from the entertainment industry, using standard Burmese. It may not fully represent the linguistic diversity of all regional dialects in Myanmar.

---

### ✅ But Here's the Strength

Even with a conservative estimate of data quality, you are likely left with over **150,000 to 170,000 high-quality speech chunks**.

That alone makes this one of the **largest publicly available Burmese speech datasets** in the world.

It is not perfect — but it is powerful.
It is not corrected — but it is real.
And real voices have always mattered more than perfect ones.

## 📄 License

This dataset is released under a **Fair Use / Research-Only License**.

It is intended for:

- ✅ Non-commercial research
- ✅ Educational use
- ✅ Language preservation
- ✅ Open AI development for Burmese (Myanmar) speech

All content was sourced from **Media Queen Entertainment's** public channels. For any commercial inquiries, please contact the original content owner directly.

For full details, see the `LICENSE` file in this repository.

## 📚 Citation

```bibtex
@misc{freococo_2025_mediaqueen,
  author       = {freococo},
  title        = {Media Queen Entertainment Voices: A Large-Scale Dataset for Burmese ASR},
  year         = {2025},
  howpublished = {Hugging Face Datasets},
  url          = {https://huggingface.co/datasets/freococo/media_queen_entertaiment_voices}
}
```
```