DatasetLwaziANV

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Modelfacebook/omniASR-CTC-1BOpen4facebook/omniASR-CTC-300MOpen4facebook/omniASR-CTC-3BOpen4facebook/omniASR-CTC-7BOpen4facebook/omniASR-LLM-1BOpen4facebook/omniASR-LLM-300MOpen1facebook/omniASR-LLM-3BOpen4facebook/omniASR-LLM-7BOpen2aadel4/omniASR-CTC-1B-v2Open5aadel4/omniASR-CTC-300M-v2Open5badrex/w2v-bert-2.0-zulu-asrOpen2dsfsi/anv-whisper-large-v3-turbo-anv-zulOpen2dsfsi/anv-whisper-small-anv-zulu-first-batchOpen6facebook/mms-1b-allOpen3openai/whisper-large-v3Open10openai/whisper-smallOpen9sitwala/whisper-large-anv-sotOpen12sitwala/whisper-large-v3-anv-sotOpen13sitwala/whisper-large-v3-turbo-anv-zul-150hOpen4sitwala/whisper-large-v3-turbo-anv-zul-250hOpen4sitwala/whisper-large-v3-turbo-anv-zul-50hOpen5

What did the model get wrong?

facebook/omniASR-LLM-3BOpen   Example 21 of 100  ·  sample index 20

✅ What was actually said (isiZulu reference)
Dolly,he,he,ngisemncanem-maukubangingacabangangalokho.
🤖 What this model heard
heyheyngisemncanemaukubangingacabangangalokho
Correct
Wrong (different word)
Missed (skipped)
Extra (added)
5
Correct
2
Wrong
2
Missed
0
Extra
56%
Words right
0.556
WER
0.210
CER
7.54s
Duration
0.5s
Latency