Datasetpublic

datadriven-company/TTS-Hungarian

TTS-Hungarian A large-scale, high-quality Hungarian speech dataset for text-to-speech and automatic speech recognition. Data Source Derived from MEK (Magyar Elektronikus Könyvtár) — Hungarian audiobooks. Dataset Statistics Metric Value Total samples 253,116 Total duration 702 hours Unique speakers 100 Average duration 10.0 seconds Average DNSMOS 3.68 Features Field Type Description __key__ string… See the full description on the dataset page: https://huggingface.co/datasets/datadriven-company/TTS-Hungarian.

sourceHugging Faceotherupdated 7mo agoView on Hugging Face

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Dataset Card

TTS-Hungarian

A large-scale, high-quality Hungarian speech dataset for text-to-speech and automatic speech recognition.

Data Source

Derived from [MEK (Magyar Elektronikus Könyvtár)](https://mek.oszk.hu/) — Hungarian audiobooks.

Dataset Statistics

Metric	Value
Total samples	253,116
Total duration	702 hours
Unique speakers	100
Average duration	10.0 seconds
Average DNSMOS	3.68

Features

Field	Type	Description
`__key__`	string	Unique sample identifier
`mp3`	Audio	Audio (24kHz mono WAV)
`text`	string	Transcription
`language`	string	Language code (`hu`)
`speaker_id`	string	Speaker/audiobook identifier
`gender`	string	`male`, `female`, or `unknown`
`dnsmos`	float	Audio quality score (1-5)

Usage

python

from datasets import load_dataset

ds = load_dataset("datadriven-company/TTS-Hungarian", split="train")

# Access a sample
sample = ds[0]
print(sample["text"])
# Audio: sample["mp3"]

License

other