Datasets:

freococo
/

media_queen_entertaiment_voices

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.

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

@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}
}