Datasetpublic

eduardem/lili-romanian-single-speaker-piper

Lili Romanian Single-Speaker Piper Dataset A curated Romanian single-speaker speech dataset prepared for Piper training. Segments 10,738 Total duration 22.91 hours Speaker Lili Gender female Language Romanian (ro) Audio format WAV, 16-bit, mono, 22.05 kHz Segment duration 2.52 - 9.99 seconds Summary This dataset contains a single Romanian narrator exposed as Lili. It is published as a Hugging Face Parquet-backed audio dataset, so the… See the full description on the dataset page: https://huggingface.co/datasets/eduardem/lili-romanian-single-speaker-piper.

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Dataset Card

Lili Romanian Single-Speaker Piper Dataset

A curated Romanian single-speaker speech dataset prepared for Piper training.


Segments	10,738
Total duration	22.91 hours
Speaker	Lili
Gender	female
Language	Romanian (ro)
Audio format	WAV, 16-bit, mono, 22.05 kHz
Segment duration	2.52 - 9.99 seconds

Summary

This dataset contains a single Romanian narrator exposed as Lili. It is published as a Hugging Face Parquet-backed audio dataset, so the Hub viewer can stream rows directly and play audio inline.

Dataset Structure

Column	Type	Description
`audio`	Audio	WAV audio sample
`text`	string	Romanian transcript
`speaker`	string	Speaker name
`gender`	string	Speaker gender
`duration`	float	Duration in seconds
`source`	string	Broad source type (`audiobook`)
`source_id`	string	Original book/narrator bucket id from the upstream dataset
`dnsmos`	float	Quality score retained from preprocessing
`clip_key`	string	Stable clip identifier

Source Dataset

This dataset is a processed derivative of `datadriven-company/TTS-Romanian`. The final speaker pool was consolidated from the following matched source ids:

—cartia_478_Florian_Cristescu_Familia_Roademult
—cartia_486_Lloyd_Douglas_Camasa_lui_Cristos
—cartia_489_Anton_Pavlovici_Cehov_Calugarul_negru
—cartia_490_Lloyd_Douglas_Marele_Pescar
—cartia_505_Ionel_Teodoreanu_La_Medeleni_Volumul_1_Hotarul_nestatornic
—cartia_512_Ionel_Teodoreanu_La_Medeleni_Volumul_2_Drumuri

Processing

The published subset corresponds to the cleaned <=10s baseline used for Piper training.

—narrator pooling across matched audiobook ids
—global exact-text dedup before export
—edge-silence trimming
—clip-level QC filtering on noise, clipping, silence, speech rate, and transcript anomalies

Average duration: 7.68s

QC summary from the final local cleaning pass:

—kept clips: 10,738
—kept hours: 22.906
—rejected clips from the <=10s pool: 788
—rejected hours from the <=10s pool: 1.400

Usage

python

from datasets import load_dataset

ds = load_dataset("eduardem/lili-romanian-single-speaker-piper")
sample = ds["train"][0]
print(sample["text"])
print(sample["audio"]["path"])

Attribution

Please preserve attribution to `datadriven-company/TTS-Romanian` when redistributing this dataset or derivatives trained from it.