Datasets:
Tasks:
Automatic Speech Recognition
Formats:
webdataset
Languages:
Uzbek
Size:
10K - 100K
Tags:
audio
License:
Update README.md
Browse files
README.md
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@@ -5,6 +5,8 @@ task_categories:
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- automatic-speech-recognition
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language:
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- uz
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pretty_name: Uzbek Language Speech-to-Text Dataset
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size_categories:
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- 100K<n<1M
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@@ -50,7 +52,7 @@ Many examples in this dataset have trailing quotations marks, e.g "Musibat yomon
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In addition, the majority of training sentences end in punctuation ( . or ? or ! ), whereas just a small proportion do not. In the dev set, almost all sentences end in punctuation. Thus, it is recommended to append a full-stop ( . ) to the end of the small number of training examples that do not end in punctuation.
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---
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-
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from datasets import load_dataset
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ds = load_dataset("mozilla-foundation/common_voice_17", "en", use_auth_token=True)
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return batch
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ds = ds.map(prepare_dataset, desc="preprocess dataset")
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-
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---
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- automatic-speech-recognition
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language:
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- uz
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tags:
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- audio
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pretty_name: Uzbek Language Speech-to-Text Dataset
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size_categories:
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- 100K<n<1M
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In addition, the majority of training sentences end in punctuation ( . or ? or ! ), whereas just a small proportion do not. In the dev set, almost all sentences end in punctuation. Thus, it is recommended to append a full-stop ( . ) to the end of the small number of training examples that do not end in punctuation.
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---
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+
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from datasets import load_dataset
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ds = load_dataset("mozilla-foundation/common_voice_17", "en", use_auth_token=True)
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return batch
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ds = ds.map(prepare_dataset, desc="preprocess dataset")
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+
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---
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