Datasets:
license: cc-by-4.0
task_categories:
- text-to-speech
language:
- en
size_categories:
- 10K<n<100K
configs:
- config_name: dev
data_files:
- split: dev.clean
path: data/dev.clean/dev.clean*.parquet
- config_name: clean
data_files:
- split: dev.clean
path: data/dev.clean/dev.clean*.parquet
- split: test.clean
path: data/test.clean/test.clean*.parquet
- split: train.clean.100
path: data/train.clean.100/train.clean.100*.parquet
- split: train.clean.360'
path: data/train.clean.360/train.clean.360*.parquet
- config_name: other
data_files:
- split: dev.other
path: data/dev.other/dev.other*.parquet
- split: test.other
path: data/test.other/test.other*.parquet
- split: train.other.500
path: data/train.other.500/train.other.500*.parquet
- config_name: all
data_files:
- split: dev.clean
path: data/dev.clean/dev.clean*.parquet
- split: dev.other
path: data/dev.other/dev.other*.parquet
- split: test.clean
path: data/test.clean/test.clean*.parquet
- split: test.other
path: data/test.other/test.other*.parquet
- split: train.clean.100
path: data/train.clean.100/train.clean.100*.parquet
- split: train.clean.360'
path: data/train.clean.360/train.clean.360*.parquet
- split: train.other.500
path: data/train.other.500/train.other.500*.parquet
Dataset Card for LibriTTS-R
LibriTTS-R [1] is a sound quality improved version of the LibriTTS corpus (http://www.openslr.org/60/) which is a multi-speaker English corpus of approximately 585 hours of read English speech at 24kHz sampling rate, published in 2019.
Overview
This is the LibriTTS-R dataset, adapted for the datasets
library.
The dataset viewer does not seem to be functional, although most of the code here was adapted from the librispeech_asr
dataset.
Usage
Splits
There are 7 splits (dots replace dashes from the original dataset, to comply with hf naming requirements):
- dev.clean
- dev.other
- test.clean
- test.other
- train.clean.100
- train.clean.360
- train.other.500
Configurations
There are 3 configurations, each which limits the splits the load_dataset()
function will download.
The default configuration is "all".
- "dev": only the "dev.clean" split (good for testing the dataset quickly)
- "clean": contains only "clean" splits
- "other": contains only "other" splits
- "all": contains only "all" splits
Example
Loading the clean
config with only the train.clean.360
split.
load_dataset("blabble-io/libritts_r", "clean", split="train.clean.100")
Streaming is also supported.
load_dataset("blabble-io/libritts_r", streaming=True)
Columns
{
"audio": datasets.Audio(sampling_rate=24_000),
"text_normalized": datasets.Value("string"),
"text_original": datasets.Value("string"),
"speaker_id": datasets.Value("string"),
"path": datasets.Value("string"),
"chapter_id": datasets.Value("string"),
"id": datasets.Value("string"),
}
Example Row
{
'audio': {
'path': '/home/user/.cache/huggingface/datasets/downloads/extracted/5551a515e85b9e463062524539c2e1cb52ba32affe128dffd866db0205248bdd/LibriTTS_R/dev-clean/3081/166546/3081_166546_000028_000002.wav',
'array': ...,
'sampling_rate': 24000
},
'text_normalized': 'How quickly he disappeared!"',
'text_original': 'How quickly he disappeared!"',
'speaker_id': '3081',
'path': '/home/user/.cache/huggingface/datasets/downloads/extracted/5551a515e85b9e463062524539c2e1cb52ba32affe128dffd866db0205248bdd/LibriTTS_R/dev-clean/3081/166546/3081_166546_000028_000002.wav',
'chapter_id': '166546',
'id': '3081_166546_000028_000002'
}
Dataset Details
Dataset Description
- License: CC BY 4.0
Dataset Sources [optional]
- Homepage: https://www.openslr.org/141/
- Paper: https://arxiv.org/abs/2305.18802
Citation
@ARTICLE{Koizumi2023-hs,
title = "{LibriTTS-R}: A restored multi-speaker text-to-speech corpus",
author = "Koizumi, Yuma and Zen, Heiga and Karita, Shigeki and Ding,
Yifan and Yatabe, Kohei and Morioka, Nobuyuki and Bacchiani,
Michiel and Zhang, Yu and Han, Wei and Bapna, Ankur",
abstract = "This paper introduces a new speech dataset called
``LibriTTS-R'' designed for text-to-speech (TTS) use. It is
derived by applying speech restoration to the LibriTTS
corpus, which consists of 585 hours of speech data at 24 kHz
sampling rate from 2,456 speakers and the corresponding
texts. The constituent samples of LibriTTS-R are identical
to those of LibriTTS, with only the sound quality improved.
Experimental results show that the LibriTTS-R ground-truth
samples showed significantly improved sound quality compared
to those in LibriTTS. In addition, neural end-to-end TTS
trained with LibriTTS-R achieved speech naturalness on par
with that of the ground-truth samples. The corpus is freely
available for download from
\textbackslashurl\{http://www.openslr.org/141/\}.",
month = may,
year = 2023,
copyright = "http://creativecommons.org/licenses/by-nc-nd/4.0/",
archivePrefix = "arXiv",
primaryClass = "eess.AS",
eprint = "2305.18802"
}