README.md

---
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

<!-- Provide a quick summary of the dataset. -->

LibriTTS is a multi-speaker English corpus of approximately 585 hours of read English speech at 24kHz sampling rate, 
prepared by Heiga Zen with the assistance of Google Speech and Google Brain team members. The LibriTTS corpus is 
designed for TTS research. It is derived from the original materials (mp3 audio files from LibriVox and text files 
from Project Gutenberg) of the LibriSpeech corpus.

## Overview

This is the LibriTTS 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", "clean", split="train.clean.100")
```

Streaming is also supported.
```
load_dataset("blabble-io/libritts", 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/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/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/60/
- **Paper:** https://arxiv.org/abs/1904.02882

## 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{Zen2019-kz,
  title         = "{LibriTTS}: A corpus derived from {LibriSpeech} for
                   text-to-speech",
  author        = "Zen, Heiga and Dang, Viet and Clark, Rob and Zhang, Yu and
                   Weiss, Ron J and Jia, Ye and Chen, Zhifeng and Wu, Yonghui",
  abstract      = "This paper introduces a new speech corpus called
                   ``LibriTTS'' designed for text-to-speech use. It is derived
                   from the original audio and text materials of the
                   LibriSpeech corpus, which has been used for training and
                   evaluating automatic speech recognition systems. The new
                   corpus inherits desired properties of the LibriSpeech corpus
                   while addressing a number of issues which make LibriSpeech
                   less than ideal for text-to-speech work. The released corpus
                   consists of 585 hours of speech data at 24kHz sampling rate
                   from 2,456 speakers and the corresponding texts.
                   Experimental results show that neural end-to-end TTS models
                   trained from the LibriTTS corpus achieved above 4.0 in mean
                   opinion scores in naturalness in five out of six evaluation
                   speakers. The corpus is freely available for download from
                   http://www.openslr.org/60/.",
  month         =  apr,
  year          =  2019,
  copyright     = "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
  archivePrefix = "arXiv",
  primaryClass  = "cs.SD",
  eprint        = "1904.02882"
}
```