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Update README.md (#1)

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- Update README.md (3cf9eaf4079ffb411fa83e416ea690823b4cdda6)


Co-authored-by: Dmitry C <literate-goggles@users.noreply.huggingface.co>

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  1. README.md +1 -1
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@@ -224,7 +224,7 @@ The model in this collection is trained on a composite dataset (NeMo ASRSet En)
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  The performance of Automatic Speech Recognition models is measuring using Word Error Rate. Since this dataset is trained on multiple domains and a much larger corpus, it will generally perform better at transcribing audio in general.
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- The following tables summarizes the performance of the available models in this collection with the Transducer decoder. Performances of the ASR models are reported in terms of Word Error Rate (WER%) with greedy decoding.
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  |**Version**|**Tokenizer**|**Vocabulary Size**|**LS test-other**|**LS test-clean**|**WSJ Eval92**|**WSJ Dev93**|**NSC Part 1**|**MLS Test**|**MCV Test 7.0**| Train Dataset |
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  |---------|-----------------------|-----------------|---------------|---------------|------------|-----------|-----|-------|------|------|
 
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  The performance of Automatic Speech Recognition models is measuring using Word Error Rate. Since this dataset is trained on multiple domains and a much larger corpus, it will generally perform better at transcribing audio in general.
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+ The following tables summarizes the performance of the available models in this collection with the ctc decoder. Performances of the ASR models are reported in terms of Word Error Rate (WER%) with greedy decoding.
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  |**Version**|**Tokenizer**|**Vocabulary Size**|**LS test-other**|**LS test-clean**|**WSJ Eval92**|**WSJ Dev93**|**NSC Part 1**|**MLS Test**|**MCV Test 7.0**| Train Dataset |
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  |---------|-----------------------|-----------------|---------------|---------------|------------|-----------|-----|-------|------|------|