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@@ -230,6 +230,18 @@ The list of the available models in this collection is shown in the following ta
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  ## Limitations
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  Since this model was trained on publicly available speech datasets, the performance of this model might degrade for speech which includes technical terms, or vernacular that the model has not been trained on. The model might also perform worse for accented speech.
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  ## References
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  [1] [Conformer: Convolution-augmented Transformer for Speech Recognition](https://arxiv.org/abs/2005.08100)
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  [2] [Google Sentencepiece Tokenizer](https://github.com/google/sentencepiece)
 
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  ## Limitations
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  Since this model was trained on publicly available speech datasets, the performance of this model might degrade for speech which includes technical terms, or vernacular that the model has not been trained on. The model might also perform worse for accented speech.
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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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+ Additionally, Riva provides:
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+ * World-class out-of-the-box accuracy for the most common languages with model checkpoints trained on proprietary data with hundreds of thousands of GPU-compute hours
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+ * Best in class accuracy with run-time word boosting (e.g., brand and product names) and customization of acoustic model, language model, and inverse text normalization
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+ * Streaming speech recognition, Kubernetes compatible scaling, and enterprise-grade support
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+ Although this model isn’t supported yet by Riva, the [list of supported models is here](https://huggingface.co/models?other=Riva).
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+ Check out [Riva live demo](https://developer.nvidia.com/riva#demos).
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  ## References
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  [1] [Conformer: Convolution-augmented Transformer for Speech Recognition](https://arxiv.org/abs/2005.08100)
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  [2] [Google Sentencepiece Tokenizer](https://github.com/google/sentencepiece)