mythicinfinity/libritts_r

---
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"
}
```