Datasets:
Tasks:
Automatic Speech Recognition
Formats:
parquet
Languages:
Azerbaijani
Size:
100K - 1M
DOI:
License:
File size: 1,926 Bytes
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---
license: cc-by-nc-4.0
task_categories:
- automatic-speech-recognition
language:
- az
tags:
- speech
- audio
- azerbaijani
- asr
size_categories:
- 100K<n<1M
pretty_name: Azerbaijani ASR Dataset
---
# Azerbaijani ASR Dataset
## Dataset Description
This dataset contains Azerbaijani speech data for Automatic Speech Recognition (ASR) tasks.
### Dataset Summary
- **Language**: Azerbaijani (az)
- **Task**: Automatic Speech Recognition
- **Total Duration**: ~334 hours
- **Total Samples**: ~351,000 audio-text pairs
- **Audio Format**: WAV, 16kHz sampling rate
- **License**: CC-BY-NC-4.0
### Dataset Structure
Each audio segment is specially numbered so that you can merge them if you need to create longer segments.
```python
DatasetDict({
train: Dataset({
features: ['audio', 'text', 'duration', 'audio_file'],
num_rows: [total_samples]
})
})
```
### Features
- `audio`: Audio file (WAV format, 16kHz)
- `text`: Transcription of the audio (Azerbaijani text)
- `duration`: Duration of audio clip in seconds
- `audio_file`: Original filename of the audio segment
### Usage
```python
from datasets import load_dataset
# Load the dataset
dataset = load_dataset("LocalDoc/azerbaijani_asr")
# Access train split
train_dataset = dataset["train"]
# Example usage
for example in train_dataset:
audio = example["audio"]
text = example["text"]
duration = example["duration"]
```
### Duration Distribution
- 0-2 sec: 36.1%
- 2-5 sec: 47.2%
- 5-10 sec: 14.6%
- 10-20 sec: 2.0%
- 20+ sec: 0.1%
### Use Cases
- Fine-tuning Whisper models for Azerbaijani
- Training new ASR models for Azerbaijani language
- Benchmarking ASR performance on Azerbaijani
### Citation
If you use this dataset, please cite:
```
@dataset{azerbaijani_asr_2025,
title={Azerbaijani ASR Dataset},
author={LocalDoc},
year={2025},
url={https://huggingface.co/datasets/LocalDoc/azerbaijani_asr}
}
``` |