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xls-r-300m-danish-nst-cv9

Automatic Speech Recognition Transformers PyTorch Safetensors

Danish wav2vec2 speech-to-text Inference Endpoints

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KennethEnevoldsen commited on Sep 12, 2022

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 ## Performance
 The table below shows the WER rate (greedy, no language model) of four different Danish ASR models on three publicly available datasets (lower is better).
-|Model                                  | [Alvenir](https://huggingface.co/datasets/Alvenir/alvenir_asr_da_eval)|   [NST (greedy)](https://www.nb.no/sprakbanken/en/resource-catalogue/oai-nb-no-sbr-19/)|     [CV9.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_9_0)|
 |:--------------------------------------|------:|-----:|-----:|
 |[Alvenir/wav2vec2-base-da-ft-nst](https://huggingface.co/Alvenir/wav2vec2-base-da-ft-nst)        |  0.202| 0.099| 0.238|
 |[chcaa/alvenir-wav2vec2-base-da-nst-cv9](https://huggingface.co/chcaa/alvenir-wav2vec2-base-da-nst-cv9) |  0.233| 0.126| 0.256|

 ## Performance
 The table below shows the WER rate (greedy, no language model) of four different Danish ASR models on three publicly available datasets (lower is better).
+|Model                                  | [Alvenir](https://huggingface.co/datasets/Alvenir/alvenir_asr_da_eval)|   [NST](https://www.nb.no/sprakbanken/en/resource-catalogue/oai-nb-no-sbr-19/)|     [CV9.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_9_0)|
 |:--------------------------------------|------:|-----:|-----:|
 |[Alvenir/wav2vec2-base-da-ft-nst](https://huggingface.co/Alvenir/wav2vec2-base-da-ft-nst)        |  0.202| 0.099| 0.238|
 |[chcaa/alvenir-wav2vec2-base-da-nst-cv9](https://huggingface.co/chcaa/alvenir-wav2vec2-base-da-nst-cv9) |  0.233| 0.126| 0.256|