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README.md
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README.md
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@ -7,16 +7,14 @@ metrics:
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- wer
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- cer
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tags:
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- en
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- audio
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- automatic-speech-recognition
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- en
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- hf-asr-leaderboard
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- mozilla-foundation/common_voice_6_0
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- robust-speech-event
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- speech
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- xlsr-fine-tuning-week
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- robust-speech-event
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- mozilla-foundation/common_voice_6_0
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- hf-asr-leaderboard
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- hf-asr-leaderboard
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- hf-asr-leaderboard
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license: apache-2.0
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model-index:
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- name: XLSR Wav2Vec2 English by Jonatas Grosman
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@ -63,9 +61,9 @@ model-index:
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value: 11.01
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---
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# Wav2Vec2-Large-XLSR-53-English
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# Fine-tuned XLSR-53 large model for speech recognition in English
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Fine-tuned [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on English using the [Common Voice](https://huggingface.co/datasets/common_voice).
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Fine-tuned [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on English using the train and validation splits of [Common Voice 6.1](https://huggingface.co/datasets/common_voice).
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When using this model, make sure that your speech input is sampled at 16kHz.
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This model has been fine-tuned thanks to the GPU credits generously given by the [OVHcloud](https://www.ovhcloud.com/en/public-cloud/ai-training/) :)
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@ -158,11 +156,9 @@ python eval.py --model_id jonatasgrosman/wav2vec2-large-xlsr-53-english --datase
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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{grosman2021wav2vec2-large-xlsr-53-english,
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title={XLSR Wav2Vec2 English by Jonatas Grosman},
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@misc{grosman2021xlsr53-large-english,
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title={Fine-tuned {XLSR}-53 large model for speech recognition in {E}nglish},
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author={Grosman, Jonatas},
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publisher={Hugging Face},
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journal={Hugging Face Hub},
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howpublished={\url{https://huggingface.co/jonatasgrosman/wav2vec2-large-xlsr-53-english}},
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year={2021}
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}
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