nvidia
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stt_it_conformer_ctc_large

Automatic Speech Recognition

hf-asr-leaderboard

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igitman commited on Oct 25, 2022

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@@ -192,7 +192,7 @@ The list of the available models in this collection is shown in the following ta
 | Version | Tokenizer             | Vocabulary Size | MCV 11.0 Dev | MCV 11.0 Test | MLS Dev | MLS Test | VoxPopuli Dev | VoxPopuli Test | Train Dataset   |
 |---------|-----------------------|-----------------|--------------|---------------|---------|----------|---------------|----------------|-----------------|
-| 1.0.0   | SentencePiece Unigram | 128             | 6.65         | 7.20          | 14.77   | 11.76    | 14.77         | 18.06          | NeMo ASRSET 2.0 |
 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.

 | Version | Tokenizer             | Vocabulary Size | MCV 11.0 Dev | MCV 11.0 Test | MLS Dev | MLS Test | VoxPopuli Dev | VoxPopuli Test | Train Dataset   |
 |---------|-----------------------|-----------------|--------------|---------------|---------|----------|---------------|----------------|-----------------|
+| 1.13.0  | SentencePiece Unigram | 128             | 6.65         | 7.20          | 14.77   | 11.76    | 14.77         | 18.06          | NeMo ASRSET 2.0 |
 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.