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RobotsMali
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stt-bm-quartznet15x5-v0

Automatic Speech Recognition
NeMo
PyTorch
Bambara
speech
audio
CTC
QuartzNet
Bambara
NeMo
Eval Results (legacy)
Model card Files
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(bam-asr-all) en ( bam-asr-early)

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@@ -108,7 +108,7 @@ This model was fine-tuned on the [bam-asr-early](https://huggingface.co/datasets
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  The performance of Automatic Speech Recognition models is measured using **Word Error Rate (WER%)**.
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- |**Version**|**Tokenizer**|**Vocabulary Size**|**bam-asr-all (test set)**|
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  |---------|-----------------------|-----------------|---------|
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  | V2 | Character-wise | 45 | 46.5 |
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  The performance of Automatic Speech Recognition models is measured using **Word Error Rate (WER%)**.
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+ |**Version**|**Tokenizer**|**Vocabulary Size**|**bam-asr-early (test set)**|
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  |---------|-----------------------|-----------------|---------|
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  | V2 | Character-wise | 45 | 46.5 |
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