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README.md
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---
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dataset_info:
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features:
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- name: audio
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- split: train
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path: data/train-*
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---
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---
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pretty_name: 10K hours of English MLS
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annotations_creators:
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- expert-generated
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language_creators:
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- crowdsourced
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- expert-generated
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language:
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- en
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license:
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- cc-by-4.0
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multilinguality:
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- multilingual
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paperswithcode_id: multilingual-librispeech
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size_categories:
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- 1M<n<10M
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source_datasets:
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- original
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task_categories:
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- automatic-speech-recognition
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- text-to-speech
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- text-to-audio
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dataset_info:
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features:
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- name: audio
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- split: train
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path: data/train-*
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---
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### Dataset Summary
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This is a **10K hours** subset of [**English version of the Multilingual LibriSpeech (MLS) dataset**](https://huggingface.co/datasets/parler-tts/mls_eng=.
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The data archives were restructured from the original ones from [OpenSLR](http://www.openslr.org/94) to make it easier to stream.
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MLS dataset is a large multilingual corpus suitable for speech research. The dataset is derived from read audiobooks from LibriVox and consists of
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8 languages - English, German, Dutch, Spanish, French, Italian, Portuguese, Polish. It includes about 44.5K hours of English and a total of about 6K hours for other languages.
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This dataset card includes the 10K hours of English. Refers to this [dataset card](https://huggingface.co/datasets/facebook/multilingual_librispeech) for the other languages.
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### Licensing Information
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Public Domain, Creative Commons Attribution 4.0 International Public License ([CC-BY-4.0](https://creativecommons.org/licenses/by/4.0/legalcode))
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### Citation Information
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```
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@article{Pratap2020MLSAL,
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title={MLS: A Large-Scale Multilingual Dataset for Speech Research},
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author={Vineel Pratap and Qiantong Xu and Anuroop Sriram and Gabriel Synnaeve and Ronan Collobert},
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journal={ArXiv},
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year={2020},
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volume={abs/2012.03411}
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}
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```
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