Speaker	Rows	Hours	%
`spk0LYT`	6,839	11.14	1.5%
`spk0Wob`	7,640	14.31	1.7%
`spk0e2A`	2,500	3.93	0.6%
`spk2dtl`	200	0.45	0.0%
`spk2tOy`	29,583	51.10	6.6%
`spk4Cqp`	9,622	16.59	2.2%
`spk4mVa`	2,000	5.45	0.4%
`spk7uff`	111,235	199.30	24.9%
`spk9NIQ`	10,487	19.69	2.3%
`spkAQIS`	325	0.64	0.1%
`spkAbnF`	2,524	4.77	0.6%
`spkH8xI`	21,809	54.14	4.9%
`spkNbrn`	38,949	72.99	8.7%
`spkNwwm`	2,444	4.64	0.5%
`spkRcor`	7,235	11.09	1.6%
`spkSXKk`	1,000	0.99	0.2%
`spkTP3f`	5,789	10.29	1.3%
`spkXRvj`	14,913	26.14	3.3%
`spkZM1J`	24,346	54.13	5.5%
`spkbmOH`	3,755	6.91	0.8%
`spkd19R`	1,500	1.37	0.3%
`spkeogr`	36,209	65.65	8.1%
`spkh9lU`	1,000	2.77	0.2%
`spkkTkx`	2,402	4.53	0.5%
`spknKYa`	45,712	80.15	10.2%
`spkq6OL`	4,345	8.15	1.0%
`spkrfA5`	475	1.00	0.1%
`spktqn6`	50,677	95.07	11.3%
`spkwJYN`	1,000	2.41	0.2%

Dataset Structure

Column	Type	Description
`audio`	Audio	Waveform + sampling rate (24kHz mono WAV)
`audio_path`	string	Audio filename
`text`	string	Transcript
`duration`	float	Segment duration in seconds
`snr`	float	Signal-to-noise ratio (dB)
`video_id`	string	Source identifier
`source_url`	string	Source
`start_time`	float	Segment start (seconds)
`end_time`	float	Segment end (seconds)
`speaker_id`	string	Speaker identifier

Usage

from datasets import load_dataset

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

sample = ds[0]
print(sample["text"])
print(sample["audio"])

CC-BY-4.0

Last updated: 2026-06-27 11:26 UTC