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@@ -270,6 +270,28 @@ The following tables summarizes the performance of the available models in this
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  These are greedy WER numbers without external LM. More details on evaluation can be found at [HuggingFace ASR Leaderboard](https://huggingface.co/spaces/hf-audio/open_asr_leaderboard)
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  ## NVIDIA Riva: Deployment
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  [NVIDIA Riva](https://developer.nvidia.com/riva), is an accelerated speech AI SDK deployable on-prem, in all clouds, multi-cloud, hybrid, on edge, and embedded.
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  [6] [HuggingFace ASR Leaderboard](https://huggingface.co/spaces/hf-audio/open_asr_leaderboard)
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  ## Licence
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  These are greedy WER numbers without external LM. More details on evaluation can be found at [HuggingFace ASR Leaderboard](https://huggingface.co/spaces/hf-audio/open_asr_leaderboard)
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+ ## Model Fairness Evaluation
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+ As presented in paper "Towards Measuring Fairness in AI: the Casual Conversations Dataset" for Fairness evaluation of Models, we evaluated parakeet-tdt-1.1b on the CausalConversations-v1
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+ dataset and results are reported as follows:
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+ ### Gender Bias:
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+ | Gender | Male | Female | N/A | Other |
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+ | :--- | :--- | :--- | :--- | :--- |
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+ | Num utterances | 19325 | 24532 | 926 | 33 |
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+ | % WER | 19.56 | 16.87 | 21.45 | 38.88 |
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+ ### Age Bias:
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+ | Age Group | $(18-30)$ | $(31-45)$ | $(46-85)$ | $(1-100)$ |
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+ | :--- | :--- | :--- | :--- | :--- |
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+ | Num utterances | 15956 | 14585 | 13349 | 43890 |
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+ | % WER | 17.95 | 18.28 | 17.95 | 18.06 |
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  ## NVIDIA Riva: Deployment
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  [NVIDIA Riva](https://developer.nvidia.com/riva), is an accelerated speech AI SDK deployable on-prem, in all clouds, multi-cloud, hybrid, on edge, and embedded.
 
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  [6] [HuggingFace ASR Leaderboard](https://huggingface.co/spaces/hf-audio/open_asr_leaderboard)
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+ [7] [Towards Measuring Fairness in AI: the Casual Conversations Dataset](https://arxiv.org/abs/2104.02821)
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  ## Licence
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