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  license: apache-2.0
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  widget:
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  - example_title: test Russian speech "нейросети это хорошо" (in English, "neural networks are good")
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- src: https://huggingface.co/bond005/wav2vec2-large-ru-golos/resolve/main/test_sound_ru.flac
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  model-index:
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  - name: XLSR Wav2Vec2 Russian with Language Model by Ivan Bondarenko
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  results:
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  The Wav2Vec2 model is based on [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53), fine-tuned in Russian using [Sberdevices Golos](https://huggingface.co/datasets/SberDevices/Golos) with audio augmentations like as pitch shift, acceleration/deceleration of sound, reverberation etc.
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- The 2-gram language model is built on the Russian text corpus obtained from six open sources:
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  - random 10% subset of [Taiga](https://tatianashavrina.github.io/taiga_site)
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  - [Russian Wikipedia](https://ru.wikipedia.org)
 
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  license: apache-2.0
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  widget:
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  - example_title: test Russian speech "нейросети это хорошо" (in English, "neural networks are good")
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+ src: https://huggingface.co/bond005/wav2vec2-large-ru-golos-with-lm/resolve/main/test_sound_ru.flac
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  model-index:
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  - name: XLSR Wav2Vec2 Russian with Language Model by Ivan Bondarenko
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  results:
 
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  The Wav2Vec2 model is based on [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53), fine-tuned in Russian using [Sberdevices Golos](https://huggingface.co/datasets/SberDevices/Golos) with audio augmentations like as pitch shift, acceleration/deceleration of sound, reverberation etc.
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+ The 2-gram language model is built on the Russian text corpus obtained from three open sources:
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  - random 10% subset of [Taiga](https://tatianashavrina.github.io/taiga_site)
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  - [Russian Wikipedia](https://ru.wikipedia.org)