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# Dataset_STT
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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`.
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## Dataset Structure
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Dataset_STT/
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βββ audio/
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β βββ uz/
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β β βββ test/
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β β β βββ test.tar
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β β βββ train/
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β β β βββ train.tar
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β β βββ validation/
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β β βββ validation.tar
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βββ transcript/
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β βββ uz/
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β β βββ test/
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β β β βββ test.tsv
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β β βββ train/
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β β β βββ train.tsv
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β β βββ validation/
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β β βββ validation.tsv
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## Files Description
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- **Audio Files:**
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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).
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- **Transcript Files:**
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The transcript files are provided in TSV format with the following columns:
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- `id`
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- `path` (the filename of the audio file within the tar archive)
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- `sentence` (the transcription)
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- `duration` (audio duration in seconds)
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- `age`
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- `gender`
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- `accents`
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- `locale`
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- **Custom Loader (`dataset_stt.py`):**
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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.
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## How to Load the Dataset
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You can load the dataset using the Hugging Face `datasets` library. For example:
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```python
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from datasets import load_dataset
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data_files = {
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"train": {"audio": "audio/uz/train/train.tar", "transcript": "transcript/uz/train/train.tsv"},
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"test": {"audio": "audio/uz/test/test.tar", "transcript": "transcript/uz/test/test.tsv"},
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"validation": {"audio": "audio/uz/validation/validation.tar", "transcript": "transcript/uz/validation/validation.tsv"}
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}
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dataset = load_dataset("Elyordev/Dataset_STT", data_files=data_files)
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print(dataset)
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