imedennikov
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Update README.md
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README.md
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@@ -178,7 +178,7 @@ The model was trained on ReazonSpeech v2.0 [5] speech corpus containing more tha
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The following table summarizes the performance of this model in terms of Character Error Rate (CER%).
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In CER calculation, punctuation marks and non-alphabet characters are removed, and
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|**Version**|**Decoder**|**JSUT basic5000**|**MCV 8.0 test**|**MCV 16.1 dev**|**MCV16.1 test**|**TEDxJP-10k**|
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The following table summarizes the performance of this model in terms of Character Error Rate (CER%).
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In CER calculation, punctuation marks and non-alphabet characters are removed, and numbers are transformed to words using `num2words` library [6].
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|**Version**|**Decoder**|**JSUT basic5000**|**MCV 8.0 test**|**MCV 16.1 dev**|**MCV16.1 test**|**TEDxJP-10k**|
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