# Dataset_STT

This dataset is designed for speech-to-text (STT) tasks and contains audio files along with their corresponding transcripts for the Uzbek language. The dataset is organized into two main directories: one for the audio files and another for the transcript files. Each of these directories is further divided by language (`uz`) and by the data split: `train`, `test`, and `validation`.

## Dataset Structure

Dataset_STT/
├── audio/
│   ├── uz/
│   │   ├── test/
│   │   │   └── test.tar 
│   │   ├── train/
│   │   │   └── train.tar 
│   │   └── validation/
│   │       └── validation.tar 
├── transcript/
│   ├── uz/
│   │   ├── test/
│   │   │   └── test.tsv
│   │   ├── train/
│   │   │   └── train.tsv
│   │   └── validation/
│   │       └── validation.tsv


## Files Description

- **Audio Files:**  
  The audio files are stored as tar archives for each data split (train, test, and validation). Each tar archive contains the actual audio recordings (e.g., in MP3 format).

- **Transcript Files:**  
  The transcript files are provided in TSV format with the following columns:
  - `id`
  - `path` (the filename of the audio file within the tar archive)
  - `sentence` (the transcription)
  - `duration` (audio duration in seconds)
  - `age`
  - `gender`
  - `accents`
  - `locale`

- **Custom Loader (`dataset_stt.py`):**  
  This script extracts audio files from the tar archives and pairs them with their metadata from the transcript TSV files. It returns the audio data using the `datasets.Audio` feature (with a sampling rate of 16000 Hz), which enables interactive playback in the Hugging Face dataset viewer.

## How to Load the Dataset

You can load the dataset using the Hugging Face `datasets` library. For example:

```python
from datasets import load_dataset

data_files = {
    "train": {"audio": "audio/uz/train/train.tar", "transcript": "transcript/uz/train/train.tsv"},
    "test": {"audio": "audio/uz/test/test.tar", "transcript": "transcript/uz/test/test.tsv"},
    "validation": {"audio": "audio/uz/validation/validation.tar", "transcript": "transcript/uz/validation/validation.tsv"}
}

dataset = load_dataset("Elyordev/Dataset_STT", data_files=data_files)
print(dataset)