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