DatasetLwaziANV

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Modelfacebook/omniASR-CTC-1BOpen4facebook/omniASR-CTC-300MOpen4facebook/omniASR-CTC-3BOpen4facebook/omniASR-CTC-7BOpen4facebook/omniASR-LLM-1BOpen3facebook/omniASR-LLM-300MOpen6facebook/omniASR-LLM-3BOpen4facebook/omniASR-LLM-7BOpen2aadel4/omniASR-CTC-1B-v2Open5aadel4/omniASR-CTC-300M-v2Open4badrex/w2v-bert-2.0-zulu-asrOpen4dsfsi/anv-whisper-large-v3-turbo-anv-zulOpen5dsfsi/anv-whisper-small-anv-zulu-first-batchOpen5facebook/mms-1b-allOpen7openai/whisper-large-v3Open11openai/whisper-smallOpen10sitwala/whisper-large-anv-sotOpen17sitwala/whisper-large-v3-anv-sotOpen18sitwala/whisper-large-v3-turbo-anv-zul-150hOpen5sitwala/whisper-large-v3-turbo-anv-zul-250hOpen5sitwala/whisper-large-v3-turbo-anv-zul-50hOpen7

What did the model get wrong?

aadel4/omniASR-CTC-300M-v2Open   Example 89 of 100  ·  sample index 88

✅ What was actually said (isiZulu reference)
ingelosikaNku-kaNkulunkuluyamemeza,kuHagari,isezulwiniyathikuye,KuyiniHagari.
🤖 What this model heard
ingolesikankulunkuluyamemezakuhangariisezulwiniyathikuyekuyinihangari
Correct
Wrong (different word)
Missed (skipped)
Extra (added)
6
Correct
3
Wrong
1
Missed
0
Extra
60%
Words right
0.600
WER
0.174
CER
8.95s
Duration
0.0s
Latency