hindi-anushka

English TTS dataset collected from YouTube using auto-generated closed captions for transcription.

Stats

Metric	Value
Total rows	332,247
Total duration	599.91 hours
Sources	378 videos
Avg segment duration	6.5s
Sample rate	24kHz mono
Format	Sharded parquet with embedded audio

Dataset Structure

Column	Type	Description
audio	Audio	Waveform + sampling rate (24kHz mono WAV)
audio_path	string	Original audio filename
text	string	Transcript from YouTube closed captions
duration	float	Segment duration in seconds
snr	float	Signal-to-noise ratio (dB)
video_id	string	YouTube video ID
source_url	string	Source URL
start_time	float	Segment start in source audio (seconds)
end_time	float	Segment end in source audio (seconds)

Usage

from datasets import load_dataset

ds = load_dataset("somu9/hindi-anushka", split="train")

sample = ds[0]
print(sample["text"])
print(sample["audio"])  # {"path": ..., "array": [...], "sampling_rate": 24000}

Collection

1. Download YouTube audio and auto-generated closed captions
2. Parse caption timestamps and merge short cues into 3-8 second segments
3. Quality filter — SNR, clipping, music detection, speaker overlap

License

CC-BY-4.0

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Last updated: 2026-05-29 10:57 UTC