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**Disclaimer:** This is a work in progress. See [VoxRex](https://huggingface.co/KBLab/wav2vec2-large-voxrex) for more details.
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**Update 2022-01-10:** Updated to VoxRex-C version.
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**Update 2022-05-16:** Paper is is [here](https://arxiv.org/abs/2205.03026).
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Finetuned version of KBs [VoxRex large](https://huggingface.co/KBLab/wav2vec2-large-voxrex) 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 **2.5%**. WER for Common Voice test set is **8.49%** directly and **7.37%** with a 4-gram language model.
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**Disclaimer:** This is a work in progress. See [VoxRex](https://huggingface.co/KBLab/wav2vec2-large-voxrex) for more details.
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**Update 2022-01-10:** Updated to VoxRex-C version.
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**Update 2022-05-16:** Paper is is [here](https://arxiv.org/abs/2205.03026).
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Finetuned version of KBs [VoxRex large](https://huggingface.co/KBLab/wav2vec2-large-voxrex) 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 **2.5%**. WER for Common Voice test set is **8.49%** directly and **7.37%** with a 4-gram language model.
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