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+*.7z filter=lfs diff=lfs merge=lfs -text
+*.arrow filter=lfs diff=lfs merge=lfs -text
+*.bin filter=lfs diff=lfs merge=lfs -text
+*.bz2 filter=lfs diff=lfs merge=lfs -text
+*.ckpt filter=lfs diff=lfs merge=lfs -text
+*.ftz filter=lfs diff=lfs merge=lfs -text
+*.gz filter=lfs diff=lfs merge=lfs -text
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+*.pcm filter=lfs diff=lfs merge=lfs -text
+*.sam filter=lfs diff=lfs merge=lfs -text
+*.raw filter=lfs diff=lfs merge=lfs -text
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+*.bmp filter=lfs diff=lfs merge=lfs -text
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libritts/README.md

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+---
+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"
+}
+```

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