Update README.md

README.md

@@ -1,4 +1,12 @@
 ---
+license: cc-by-4.0
+task_categories:
+- text-to-speech
+language:
+- en
+size_categories:
+- 10K<n<100K
+
 dataset_info:
 - config_name: clean
   features:
@@ -83,3 +91,130 @@ configs:
   - split: train.other.500
     path: other/train.other.500-*
 ---
+
+# 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"
+}
+```