README.md

---
license: cc-by-4.0
task_categories:
- automatic-speech-recognition
language:
- en
size_categories:
- 1K<n<10K
dataset_info:
  features:
  - name: audio
    dtype: audio
  - name: duration
    dtype: float64
  - name: sentence
    dtype: string
  - name: uid
    dtype: string
  - name: group_id
    dtype: string
  splits:
  - name: train
    num_bytes: 2266599053.0
    num_examples: 8000
  - name: valid
    num_bytes: 260175020.0
    num_examples: 1000
  - name: test
    num_bytes: 283822168.0
    num_examples: 1000
  download_size: 2784319038
  dataset_size: 2810596241.0
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
  - split: valid
    path: data/valid-*
  - split: test
    path: data/test-*
---

# 🎬 ScreenTalk-XS: Sample Speech Dataset from Screen Content 🖥️

![Hugging Face](https://img.shields.io/badge/HuggingFace-Dataset-blue)  
![License: CC BY-NC 4.0](https://img.shields.io/badge/License-CC%20BY--NC%204.0-orange)  
![Dataset Type: XS (Limited Version)](https://img.shields.io/badge/Access-Limited-green)  

### 📢 **What is ScreenTalk-XS?**
**ScreenTalk-XS** is a **high-quality transcribed speech dataset** containing **10k speech samples** from diverse screen content.  
It is designed for **automatic speech recognition (ASR), natural language processing (NLP), and conversational AI research**.  

✅ **This dataset is freely available for research and educational use.**  
🔹 If you need a **larger dataset with more diverse speech samples**, check out:  
👉 [ScreenTalk (Full Dataset)](https://huggingface.co/datasets/DataLabX/ScreenTalk)  

---

## 📜 **Dataset Details**
| Feature | Description |
|---------|-------------|
| **Total Clips** | 10k transcribed speech samples |
| **Languages** | English |
| **Format** | `.wav` (audio) + `.tsv` (transcriptions) |
| **Use Case** | ASR, Speech-to-Text, NLP, Conversational AI |

🆓 **This dataset is free to use for research purposes.**  

---

## 📂 **Dataset Structure**
ScreenTalk-XS contains the following fields:

| Column | Description |
|--------|-------------|
| `audio` | Audio file path |
| `sentence` | Transcribed speech |

📌 **Example Entry**
```json
{
    "audio": "path/to/audio.wav",
    "sentence": "I will find you and I will train my model."
}