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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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@@ -128,7 +128,7 @@ The performance of Automatic Speech Recognition models is measured using Word Er
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  | Benchmark | Decoding | WER (%) ↓ | CER (%) ↓ |
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  |---------------|----------|-----------------|-----------------|
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- | Bam ASR Early | CTC | **46.66** | **21.65** |
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  | Nyana Eval | CTC | 65.42 | 30.66 |
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  These are **greedy WER numbers without external LM**.
 
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  | Benchmark | Decoding | WER (%) ↓ | CER (%) ↓ |
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  |---------------|----------|-----------------|-----------------|
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+ | Bam ASR Early | CTC | 46.66 | 21.65 |
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  | Nyana Eval | CTC | 65.42 | 30.66 |
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  These are **greedy WER numbers without external LM**.