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type: cer
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value: 3.946846
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**PLEASE NOTE [This](https://huggingface.co/KBLab/wav2vec2-large-voxrex-swedish) model performs better**
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# Wav2vec 2.0 large-voxpopuli-sv-swedish
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Additionally pretrained and finetuned version of Facebooks [VoxPopuli-sv large](https://huggingface.co/facebook/wav2vec2-large-sv-voxpopuli) model using Swedish radio broadcasts, NST and Common Voice data. Evalutation without a language model gives the following: WER for NST + Common Voice test set (2% of total sentences) is **3.95%**. WER for Common Voice test set is **10.99%** directly and **7.82%** with a 4-gram language model.
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When using this model, make sure that your speech input is sampled at 16kHz.
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type: cer
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value: 3.946846
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# Wav2vec 2.0 large-voxpopuli-sv-swedish
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**PLEASE NOTE that [this](https://huggingface.co/KBLab/wav2vec2-large-voxrex-swedish) model performs better and has a less restrictive license.**
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Additionally pretrained and finetuned version of Facebooks [VoxPopuli-sv large](https://huggingface.co/facebook/wav2vec2-large-sv-voxpopuli) model using Swedish radio broadcasts, NST and Common Voice data. Evalutation without a language model gives the following: WER for NST + Common Voice test set (2% of total sentences) is **3.95%**. WER for Common Voice test set is **10.99%** directly and **7.82%** with a 4-gram language model.
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When using this model, make sure that your speech input is sampled at 16kHz.
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