nvidia
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stt_es_conformer_ctc_large

Automatic Speech Recognition

hf-asr-leaderboard

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erastorgueva-nv commited on Jul 9, 2022

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@@ -169,7 +169,7 @@ The list of the available models in this collection is shown in the following ta
 | Version | Tokenizer             | Vocabulary Size | MCV 7.0 Dev | MCV 7.0 Test | MLS Dev | MLS Test | Voxpopuli Dev | Voxpopuli Test | Fisher Dev | Fisher Test| Train Dataset   |
 |---------|-----------------------|-----------------|-------------|--------------|---------|----------|---------------|----------------|------------|-------------|-----------------|
-| 1.8.0   | SentencePiece Unigram | 1024            | 6.3         | 6.9          | 4.3     | 4.2      | 6.1           | 7.5            | 18.3.      | 18.5        | 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 7.0 Dev | MCV 7.0 Test | MLS Dev | MLS Test | Voxpopuli Dev | Voxpopuli Test | Fisher Dev | Fisher Test| Train Dataset   |
 |---------|-----------------------|-----------------|-------------|--------------|---------|----------|---------------|----------------|------------|-------------|-----------------|
+| 1.8.0   | SentencePiece Unigram | 1024            | 6.3         | 6.9          | 4.3     | 4.2      | 6.1           | 7.5            | 18.3       | 18.5        | 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.