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  value: 4.850368
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  ---
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  # Wav2vec 2.0 large-voxpopuli-sv-swedish
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- Finetuned version of Facebooks [VoxPopuli-sv large](https://huggingface.co/facebook/wav2vec2-large-sv-voxpopuli) model using 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 **6.30%**, WER for Common Voice test set is **13.59%** directly and **9.5%** with a 4-gram KenLM language model.
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  When using this model, make sure that your speech input is sampled at 16kHz.
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  value: 4.850368
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  ---
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  # Wav2vec 2.0 large-voxpopuli-sv-swedish
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+ Finetuned version of Facebooks [VoxPopuli-sv large](https://huggingface.co/facebook/wav2vec2-large-sv-voxpopuli) model using 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 **6.30%**, WER for Common Voice test set is **13.59%** directly and **9.5%** 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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