metadata

license: cc-by-4.0
task_categories:
  - automatic-speech-recognition
language:
  - en
size_categories:
  - 1K<n<10K
dataset_info:
  - config_name: default
    features:
      - name: audio
        dtype: audio
      - name: sentence
        dtype: string
      - name: __index_level_0__
        dtype: int64
      - name: uid
        dtype: string
      - name: group_id
        dtype: string
    splits:
      - name: train
        num_bytes: 808729803
        num_examples: 8000
      - name: valid
        num_bytes: 100576850
        num_examples: 1000
      - name: test
        num_bytes: 105257621
        num_examples: 1000
    download_size: 1009358769
    dataset_size: 1014564274
  - config_name: en
    features:
      - name: audio
        dtype: audio
      - name: sentence
        dtype: string
    splits:
      - name: xs
        num_bytes: 653140044
        num_examples: 10000
    download_size: 647516502
    dataset_size: 653140044
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
      - split: valid
        path: data/valid-*
      - split: test
        path: data/test-*
  - config_name: en
    data_files:
      - split: xs
        path: en/xs-*
    default: true

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

📢 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)

📜 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

{
    "audio": "path/to/audio.wav",
    "sentence": "I will find you and I will train my model."
}