Automatic Speech Recognition
NeMo
PyTorch
English
speech
audio
FastConformer
Conformer
NeMo
hf-asr-leaderboard
ctc
Eval Results
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@@ -240,7 +240,7 @@ The tokenizers for these models were built using the text transcripts of the tra
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  The model was trained on 64K hours of English speech collected and prepared by NVIDIA NeMo and Suno teams.
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- The training dataset consists of private subset with 40K hours of English speech plus 25K hours from the following public datasets:
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  - Librispeech 960 hours of English speech
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  - Fisher Corpus
 
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  The model was trained on 64K hours of English speech collected and prepared by NVIDIA NeMo and Suno teams.
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+ The training dataset consists of private subset with 40K hours of English speech plus 24K hours from the following public datasets:
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  - Librispeech 960 hours of English speech
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  - Fisher Corpus