DatasetLwaziANV

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Modelfacebook/omniASR-CTC-1BOpen5facebook/omniASR-CTC-300MOpen5facebook/omniASR-CTC-3BOpen5facebook/omniASR-CTC-7BOpen5facebook/omniASR-LLM-1BOpen5facebook/omniASR-LLM-300MOpen5facebook/omniASR-LLM-3BOpen5facebook/omniASR-LLM-7BOpen5aadel4/omniASR-CTC-1B-v2Open5aadel4/omniASR-CTC-300M-v2Open5badrex/w2v-bert-2.0-zulu-asrOpen5dsfsi/anv-whisper-large-v3-turbo-anv-zulOpen5dsfsi/anv-whisper-small-anv-zulu-first-batchOpen5facebook/mms-1b-allOpen5openai/whisper-large-v3Open11openai/whisper-smallOpen11sitwala/whisper-large-anv-sotOpen15sitwala/whisper-large-v3-anv-sotOpen13sitwala/whisper-large-v3-turbo-anv-zul-150hOpen5sitwala/whisper-large-v3-turbo-anv-zul-250hOpen5sitwala/whisper-large-v3-turbo-anv-zul-50hOpen5

What did the model get wrong?

facebook/omniASR-LLM-3BOpen   Example 60 of 100  ·  sample index 59

✅ What was actually said (isiZulu reference)
[s]emvakwesikhashana,bazibonasebece-sebegebise[s]amakhalakanyekanye.
🤖 What this model heard
emvakwesikhashanabezibonasebeqe-sebeqebiseamakhalakanyekanye
Correct
Wrong (different word)
Missed (skipped)
Extra (added)
5
Correct
3
Wrong
2
Missed
0
Extra
50%
Words right
0.625
WER
0.072
CER
8.46s
Duration
0.5s
Latency