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@@ -149,7 +149,7 @@ It is a "large" versions of Conformer-CTC (around 120M parameters) model.
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  ## NVIDIA Riva: Deployment
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- This model can be efficiently deployed with [NVIDIA Riva](https://developer.nvidia.com/riva), an accelerated speech AI SDK, on-premises, on the edge or with any cloud provider.
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  Additionally, with RIVA you get:
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  * Streaming speech recognition mode
@@ -237,8 +237,7 @@ The list of the available models in this collection is shown in the following ta
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  |---------|-----------------------|-----------------|---------------|---------------|------------|-----------|-------|------|-----|-------|---------|
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  | 1.6.0 | SentencePiece Unigram | 128 | 4.3 | 2.2 | 2.0 | 2.9 | 7.0 | 7.2 | 6.5 | 8.0 | NeMo ASRSET 2.0 |
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- You may use language models to improve the accuracy of the models. The WER(%) of the latest model with different language modeling techniques are reported in the following table.
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  | Language Modeling | Training Dataset | LS test-other | LS test-clean | Comment |
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  |-------------------------------------|-------------------------|---------------|---------------|---------------------------------------------------------|
 
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  ## NVIDIA Riva: Deployment
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+ This model can be efficiently (best latency and throughput) deployed with [NVIDIA Riva](https://developer.nvidia.com/riva), a GPU-accelerated speech AI SDK, on-premises, on the edge or with any cloud provider.
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  Additionally, with RIVA you get:
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  * Streaming speech recognition mode
 
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  |---------|-----------------------|-----------------|---------------|---------------|------------|-----------|-------|------|-----|-------|---------|
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  | 1.6.0 | SentencePiece Unigram | 128 | 4.3 | 2.2 | 2.0 | 2.9 | 7.0 | 7.2 | 6.5 | 8.0 | NeMo ASRSET 2.0 |
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+ While deploying with [NVIDIA Riva](https://developer.nvidia.com/riva), you can combine this model with external language models to further improve WER. The WER(%) of the latest model with different language modeling techniques are reported in the following table.
 
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  | Language Modeling | Training Dataset | LS test-other | LS test-clean | Comment |
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  |-------------------------------------|-------------------------|---------------|---------------|---------------------------------------------------------|