---
dataset_info:
  features:
  - name: id
    dtype: string
  - name: audio
    dtype: audio
  - name: transcription
    dtype: string
  - name: spectrogram
    dtype: image
  - name: mfcc
    sequence:
      sequence: float64
  - name: tokens
    sequence: string
  - name: token_ids
    sequence: int64
  splits:
  - name: train
    num_bytes: 56024142
    num_examples: 188
  download_size: 48514880
  dataset_size: 56024142
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
license: mit
language:
- tr
pretty_name: ' '
---






# Sayha

## YouTube Video Audio and Subtitles Extraction

Sayha is a tool designed to download YouTube videos and extract their audio and subtitle data. This can be particularly useful for creating datasets for machine learning projects, transcription services, or language studies.

## Features

- Download YouTube videos.
- Extract audio tracks from videos.
- Retrieve and process subtitle files.
- Prepare datasets for various applications.

## Installation

### Clone the Repository:

```sh
git clone https://github.com/zinderud/Sayha.git
cd Sayha
 

```
pip install -r requirements.txt

```

Usage

```
Download Videos:

Use the provided scripts to download YouTube videos. For example:

```

python [script.py](http://script.py/)

Extract Audio and Subtitles:

After downloading, run the processing scripts to extract audio and subtitles:

python colab_processor.py

Upload to Hugging Face:

If you wish to share your dataset, you can upload it to Hugging Face:

```
python upload_to_huggingface.py

```

Contributing

Contributions are welcome! Feel free to open issues or submit pull requests.
License

This project is licensed under the MIT License.