Automatic Speech Recognition
Transformers
Safetensors
German
whisper
Eval Results
Inference Endpoints
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@@ -51,12 +51,12 @@ This model can be used in various application areas, including
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  ## Evaluations - Word error rate
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- | Dataset | openai-whisper-large-v3-turbo | openai-whisper-large-v3 | primeline-whisper-large-v3-german | nyrahealth-CrisperWhisper | primeline-whisper-large-v3-turbo-german |
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- |---------------------------------|-------------------------------|-------------------------|----------------------------------|---------------------------|----------------------------------------|
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- | common_voice_19_0 | 6.31 | 5.84 | 4.30 | **4.14** | 4.28 |
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- | Tuda-De | 11.45 | 11.21 | 9.89 | 13.88 | **8.10** |
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- | multilingual librispeech | 18.03 | 17.69 | 13.46 | 10.10 | **4.71** |
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- | All | 14.16 | 13.79 | 10.51 | 8.48 | **4.75** |
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  The data and code for evaluations are available [here](https://huggingface.co/datasets/flozi00/asr-german-mixed-evals)
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  ## Evaluations - Word error rate
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+ | Dataset | openai-whisper-large-v3-turbo | openai-whisper-large-v3 | primeline-whisper-large-v3-german | nyrahealth-CrisperWhisper (large version) | primeline-whisper-large-v3-turbo-german |
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+ |-------------------------------------|-------------------------------|-------------------------|-----------------------------------|---------------------------|-----------------------------------------|
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+ | common_voice_19_0 | 3.929 | 3.559 | 3.215 | **1.925** | 3.202 |
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+ | multilingual librispeech | 3.205 | 2.833 | 2.128 | 2.847 | **2.073** |
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+ | Tuda-De | 8.331 | 7.951 | 8.285 | **5.447** | 6.577 |
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+ | All | 3.676 | 3.305 | 2.761 | 2.697 | **2.637** |
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  The data and code for evaluations are available [here](https://huggingface.co/datasets/flozi00/asr-german-mixed-evals)
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