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README.md
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@@ -259,8 +259,8 @@ The performance of Automatic Speech Recognition models is measuring using Word E
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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**|**AMI**|**Earnings-22**|**Giga Speech**|**LS test-clean**| **LS test-other** | **SPGI Speech**|**TEDLIUM-v3**|**Vox Populi**|**Common Voice**|
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| 1.23.0 | SentencePiece Unigram | 1024
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These are greedy WER numbers without external LM. More details on evaluation can be found at [HuggingFace ASR Leaderboard](https://huggingface.co/spaces/hf-audio/open_asr_leaderboard)
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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**|**AMI**|**Earnings-22**|**Giga Speech**|**LS test-clean**| **LS test-other** | **SPGI Speech**|**TEDLIUM-v3**|**Vox Populi**|**Common Voice**|
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|---------|-----------------------|-----------------|---------|---------------|------------|-----------|---------------|-------------|------|------|--------|
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| 1.23.0 | SentencePiece Unigram | 1024 | 15.94 | 11.86 | 10.19 | 1.82 | 3.67 | 2.24 | 3.87 | 6.19 | 8.69 |
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These are greedy WER numbers without external LM. More details on evaluation can be found at [HuggingFace ASR Leaderboard](https://huggingface.co/spaces/hf-audio/open_asr_leaderboard)
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