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--- |
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license: cc |
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language: |
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- pt |
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- it |
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- fr |
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- es |
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- ar |
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- he |
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- ka |
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task_categories: |
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- automatic-speech-recognition |
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pretty_name: Common Voice Corpus 15.0 |
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size_categories: |
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- 100B<n<1T |
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tags: |
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- mozilla |
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- foundation |
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--- |
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# Dataset Card for Common Voice Corpus 15.0 |
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<!-- Provide a quick summary of the dataset. --> |
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This dataset is an unofficial converted version of the Mozilla Common Voice Corpus 15. It currently contains the following languages: Arabic, Georgian, Hebrew, and Portuguese. Italian, French, and Spanish are being converted and will be uploaded in the next few days. |
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## How to use |
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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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For example, to download the Portuguese config, simply specify the corresponding language config name (i.e., "pt" for Portuguese): |
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``` |
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from datasets import load_dataset |
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cv_15 = load_dataset("fsicoli/common_voice_15_0", "pt", split="train") |
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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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``` |
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from datasets import load_dataset |
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cv_15 = load_dataset("fsicoli/common_voice_15_0", "pt", split="train", streaming=True) |
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print(next(iter(cv_15))) |
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``` |
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Bonus: create a PyTorch dataloader directly with your own datasets (local/streamed). |
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### Local |
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``` |
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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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cv_15 = load_dataset("fsicoli/common_voice_15_0", "pt", split="train") |
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batch_sampler = BatchSampler(RandomSampler(cv_15), batch_size=32, drop_last=False) |
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dataloader = DataLoader(cv_15, batch_sampler=batch_sampler) |
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``` |
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### Streaming |
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``` |
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from datasets import load_dataset |
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from torch.utils.data import DataLoader |
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cv_15 = load_dataset("fsicoli/common_voice_15_0", "pt", split="train") |
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dataloader = DataLoader(cv_15, batch_size=32) |
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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. |
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### Dataset Structure |
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Data Instances |
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A typical data point comprises the path to the audio file and its sentence. Additional fields include accent, age, client_id, up_votes, down_votes, gender, locale and segment. |
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### Licensing Information |
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Public Domain, CC-0 |
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### Citation Information |
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``` |
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@inproceedings{commonvoice:2020, |
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author = {Ardila, R. and Branson, M. and Davis, K. and Henretty, M. and Kohler, M. and Meyer, J. and Morais, R. and Saunders, L. and Tyers, F. M. and Weber, G.}, |
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title = {Common Voice: A Massively-Multilingual Speech Corpus}, |
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booktitle = {Proceedings of the 12th Conference on Language Resources and Evaluation (LREC 2020)}, |
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pages = {4211--4215}, |
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year = 2020 |
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} |
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``` |
