|
--- |
|
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 |
|
|
|
<!-- Provide a quick summary of the dataset. --> |
|
|
|
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. |
|
|
|
## 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] |
|
|
|
<!-- Provide the basic links for the dataset. --> |
|
|
|
- **Homepage:** https://www.openslr.org/141/ |
|
- **Paper:** https://arxiv.org/abs/2305.18802 |
|
|
|
## Citation |
|
|
|
<!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. --> |
|
|
|
``` |
|
@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" |
|
} |
|
``` |
