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--- |
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language: ru |
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datasets: |
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- SberDevices/Golos |
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metrics: |
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- wer |
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- cer |
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tags: |
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- audio |
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- automatic-speech-recognition |
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- speech |
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- xlsr-fine-tuning-week |
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license: apache-2.0 |
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model-index: |
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- name: XLSR Wav2Vec2 Russian by Ivan Bondarenko |
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results: |
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- task: |
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name: Speech Recognition |
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type: automatic-speech-recognition |
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dataset: |
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name: Sberdevices Golos (crowd) |
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type: SberDevices/Golos |
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args: ru |
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metrics: |
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- name: Test WER |
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type: wer |
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value: 7.985 |
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- name: Test CER |
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type: cer |
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value: 2.014 |
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- task: |
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name: Speech Recognition |
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type: automatic-speech-recognition |
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dataset: |
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name: Sberdevices Golos (farfield) |
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type: SberDevices/Golos |
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args: ru |
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metrics: |
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- name: Test WER |
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type: wer |
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value: 19.912 |
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- name: Test CER |
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type: cer |
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value: 5.904 |
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--- |
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|
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# Wav2Vec2-Large-Ru-Golos |
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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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When using this model, make sure that your speech input is sampled at 16kHz. |
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## Citation |
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If you want to cite this model you can use this: |
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```bibtex |
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@misc{bondarenko2022wav2vec2-large-ru-golos, |
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title={XLSR Wav2Vec2 Russian by Ivan Bondarenko}, |
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author={Bondarenko, Ivan}, |
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publisher={Hugging Face}, |
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journal={Hugging Face Hub}, |
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howpublished={\url{https://huggingface.co/bond005/wav2vec2-large-ru-golos}}, |
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year={2022} |
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} |
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``` |
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