DatasetLwaziANV

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Modelfacebook/omniASR-CTC-1BOpen7facebook/omniASR-CTC-300MOpen7facebook/omniASR-CTC-3BOpen5facebook/omniASR-CTC-7BOpen3facebook/omniASR-LLM-1BOpen4facebook/omniASR-LLM-300MOpen4facebook/omniASR-LLM-3BOpen3facebook/omniASR-LLM-7BOpen6aadel4/omniASR-CTC-1B-v2Open4aadel4/omniASR-CTC-300M-v2Open5badrex/w2v-bert-2.0-zulu-asrOpen2dsfsi/anv-whisper-large-v3-turbo-anv-zulOpen4dsfsi/anv-whisper-small-anv-zulu-first-batchOpen5facebook/mms-1b-allOpen4openai/whisper-large-v3Open11openai/whisper-smallOpen10sitwala/whisper-large-anv-sotOpen13sitwala/whisper-large-v3-anv-sotOpen14sitwala/whisper-large-v3-turbo-anv-zul-150hOpen3sitwala/whisper-large-v3-turbo-anv-zul-250hOpen3sitwala/whisper-large-v3-turbo-anv-zul-50hOpen5

What did the model get wrong?

facebook/omniASR-LLM-1BOpen   Example 84 of 100  ·  sample index 83

✅ What was actually said (isiZulu reference)
umakunje,nawouMnyangoweMfundo,ungekewaphumelela,ngamakomitiawo.
🤖 What this model heard
umakanjenaweumnyangowemfundoungekewaphumelelangamakomidiawu
Correct
Wrong (different word)
Missed (skipped)
Extra (added)
5
Correct
4
Wrong
0
Missed
0
Extra
56%
Words right
0.667
WER
0.113
CER
7.71s
Duration
0.4s
Latency