Update README.md

README.md

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----
-license: other
-license_name: custom
-license_link: LICENSE
----
+---
+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}
+}
+```
+```