DatasetLwaziANV

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Modelfacebook/omniASR-CTC-1BOpen13facebook/omniASR-CTC-300MOpen10facebook/omniASR-CTC-3BOpen12facebook/omniASR-CTC-7BOpen14facebook/omniASR-LLM-1BOpen12facebook/omniASR-LLM-300MOpen11facebook/omniASR-LLM-3BOpen12facebook/omniASR-LLM-7BOpen12aadel4/omniASR-CTC-1B-v2Open14aadel4/omniASR-CTC-300M-v2Open17badrex/w2v-bert-2.0-zulu-asrOpen12dsfsi/anv-whisper-large-v3-turbo-anv-zulOpen9dsfsi/anv-whisper-small-anv-zulu-first-batchOpen16facebook/mms-1b-allOpen15openai/whisper-large-v3Open17openai/whisper-smallOpen17sitwala/whisper-large-anv-sotOpen17sitwala/whisper-large-v3-anv-sotOpen20sitwala/whisper-large-v3-turbo-anv-zul-150hOpen15sitwala/whisper-large-v3-turbo-anv-zul-250hOpen9sitwala/whisper-large-v3-turbo-anv-zul-50hOpen14

What did the model get wrong?

facebook/omniASR-LLM-7BOpen   Example 43 of 100  ·  sample index 42

✅ What was actually said (isiZulu reference)
ohshagalolunyela,ohangiboni[n]kahlemos-ngathi-shagalolunye,[n]uNdasayini[n]u-u-March.
🤖 What this model heard
ohhoushiyagaloolunyelaohhoangibonikahlemosingathiushiyagaloolunyeondasayiniu-umarch
Correct
Wrong (different word)
Missed (skipped)
Extra (added)
6
Correct
8
Wrong
3
Missed
1
Extra
35%
Words right
0.857
WER
0.247
CER
5.44s
Duration
0.6s
Latency