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README updates to include code snippets and correct leaderboard URL (#6)

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- README updates to include code snippets and correct leaderboard URL (4b653d4d838af288df031ebbba95b8edd911adca)
- up (8e9b160e5190a078e2a65acb3b09175d286ff9bf)


Co-authored-by: Vaibhav Srivastav <[email protected]>

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  1. README.md +51 -1
README.md CHANGED
@@ -33,6 +33,7 @@ task_categories:
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  - [Dataset Summary](#dataset-summary)
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  - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
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  - [Languages](#languages)
 
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  - [Dataset Structure](#dataset-structure)
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  - [Data Instances](#data-instances)
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  - [Data Fields](#data-fields)
@@ -57,7 +58,7 @@ task_categories:
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  - **Homepage:** [MultiLingual LibriSpeech ASR corpus](http://www.openslr.org/94)
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  - **Repository:** [Needs More Information]
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  - **Paper:** [MLS: A Large-Scale Multilingual Dataset for Speech Research](https://arxiv.org/abs/2012.03411)
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- - **Leaderboard:** [Paperswithcode Leaderboard](https://paperswithcode.com/dataset/multilingual-librispeech)
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  ### Dataset Summary
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@@ -75,6 +76,55 @@ MLS dataset is a large multilingual corpus suitable for speech research. The dat
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  The dataset is derived from read audiobooks from LibriVox and consists of 8 languages - English, German, Dutch, Spanish, French, Italian, Portuguese, Polish
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  ## Dataset Structure
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  ### Data Instances
 
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  - [Dataset Summary](#dataset-summary)
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  - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
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  - [Languages](#languages)
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+ - [How to use](#how-to-use)
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  - [Dataset Structure](#dataset-structure)
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  - [Data Instances](#data-instances)
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  - [Data Fields](#data-fields)
 
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  - **Homepage:** [MultiLingual LibriSpeech ASR corpus](http://www.openslr.org/94)
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  - **Repository:** [Needs More Information]
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  - **Paper:** [MLS: A Large-Scale Multilingual Dataset for Speech Research](https://arxiv.org/abs/2012.03411)
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+ - **Leaderboard:** [🤗 Autoevaluate Leaderboard](https://huggingface.co/spaces/autoevaluate/leaderboards?dataset=facebook%2Fmultilingual_librispeech&only_verified=0&task=automatic-speech-recognition&config=-unspecified-&split=-unspecified-&metric=wer)
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  ### Dataset Summary
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  The dataset is derived from read audiobooks from LibriVox and consists of 8 languages - English, German, Dutch, Spanish, French, Italian, Portuguese, Polish
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+ ### How to use
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+
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+ The `datasets` library allows you to load and pre-process your dataset in pure Python, at scale. The dataset can be downloaded and prepared in one call to your local drive by using the `load_dataset` function.
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+
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+ For example, to download the German config, simply specify the corresponding language config name (i.e., "german" for German):
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+ ```python
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+ from datasets import load_dataset
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+
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+ mls = load_dataset("facebook/multilingual_librispeech", "german", split="train")
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+ ```
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+
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+ Using the datasets library, you can also stream the dataset on-the-fly by adding a `streaming=True` argument to the `load_dataset` function call. Loading a dataset in streaming mode loads individual samples of the dataset at a time, rather than downloading the entire dataset to disk.
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+ ```python
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+ from datasets import load_dataset
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+
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+ mls = load_dataset("facebook/multilingual_librispeech", "german", split="train", streaming=True)
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+
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+ print(next(iter(mls)))
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+ ```
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+
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+ *Bonus*: create a [PyTorch dataloader](https://huggingface.co/docs/datasets/use_with_pytorch) directly with your own datasets (local/streamed).
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+ Local:
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+
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+ ```python
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+ from datasets import load_dataset
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+ from torch.utils.data.sampler import BatchSampler, RandomSampler
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+
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+ mls = load_dataset("facebook/multilingual_librispeech", "german", split="train")
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+ batch_sampler = BatchSampler(RandomSampler(mls), batch_size=32, drop_last=False)
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+ dataloader = DataLoader(mls, batch_sampler=batch_sampler)
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+ ```
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+
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+ Streaming:
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+
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+ ```python
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+ from datasets import load_dataset
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+ from torch.utils.data import DataLoader
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+
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+ mls = load_dataset("facebook/multilingual_librispeech", "german", split="train", streaming=True)
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+ dataloader = DataLoader(mls, batch_size=32)
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+ ```
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+
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+ To find out more about loading and preparing audio datasets, head over to [hf.co/blog/audio-datasets](https://huggingface.co/blog/audio-datasets).
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+
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+ ### Example scripts
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+
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+ Train your own CTC or Seq2Seq Automatic Speech Recognition models on MultiLingual Librispeech with `transformers` - [here](https://github.com/huggingface/transformers/tree/main/examples/pytorch/speech-recognition).
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+
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  ## Dataset Structure
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  ### Data Instances