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--- |
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base_model: facebook/wav2vec2-xls-r-300m |
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language: |
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- uk |
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license: "apache-2.0" |
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tags: |
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- automatic-speech-recognition |
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datasets: |
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- mozilla-foundation/common_voice_10_0 |
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metrics: |
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- wer |
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model-index: |
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- name: w2v-xls-r-uk |
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results: |
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- task: |
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name: Automatic Speech Recognition |
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type: automatic-speech-recognition |
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dataset: |
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name: common_voice_10_0 |
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type: common_voice_10_0 |
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config: uk |
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split: test |
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args: uk |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.0463 |
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--- |
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🚨🚨🚨 **ATTENTION!** 🚨🚨🚨 |
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**Use an updated model**: https://huggingface.co/Yehor/w2v-bert-uk-v2.1 |
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--- |
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## Community |
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- Discord: https://discord.gg/yVAjkBgmt4 |
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- Speech Recognition: https://t.me/speech_recognition_uk |
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- Speech Synthesis: https://t.me/speech_synthesis_uk |
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## Overview |
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This model has apostrophes and hyphens. |
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The language model is trained on the texts of the Common Voice dataset, which is used during training. |
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Metrics: |
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| Dataset | CER | WER | |
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|-|-|-| |
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| CV7 (no LM) | 0.0432 | 0.2288 | |
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| CV7 (with LM) | 0.0169 | 0.0706 | |
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| CV10 (no LM) | 0.0412 | 0.2206 | |
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| CV10 (with LM) | 0.0118 | 0.0463 | |
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