---
license: apache-2.0
task_categories:
- text-to-speech
language:
- ur
size_categories:
- 10K<n<100K
---



# Urdu TTS Dataset

A high-quality Urdu speech dataset for Text-to-Speech (TTS) model training,
built from YouTube audiobooks and narrations.

## Dataset Statistics

| Property | Value |
|---|---|
| Language | Urdu (ur) |
| Total Samples | 50000 |
| Total Duration | 70 hours |
| Sample Rate | 22050 Hz |
| Audio Format | WAV (16-bit PCM, mono) |

## Columns

| Column | Type | Description |
|---|---|---|
| `audio` | Audio | WAV file at 22050 Hz |
| `transcript` | string | Raw Urdu transcription (Whisper) |
| `normalized_text` | string | Cleaned and normalized Urdu text |
| `audio_id` | string | Unique segment identifier |
| `duration_sec` | float | Clip duration in seconds |
| `snr_db` | float | Estimated signal-to-noise ratio |
| `source_file` | string | Source YouTube video filename |
| `language` | string | Always `"ur"` |

## Usage

```python
from datasets import load_dataset

dataset = load_dataset("{repo_id}")
print(dataset["train"][0])
```

## Pipeline

1. YouTube audio download (yt-dlp)
2. Voice Activity Detection segmentation (1.5–15 sec clips)
3. SNR quality filtering
4. Urdu transcription (OpenAI Whisper medium/large)
5. Text normalization and deduplication
6. Incremental shard upload to HuggingFace

## License

CC BY 4.0 — Please respect the rights of original content creators.