Dataset
Lwazi
ANV
← All examples
Model summary →
Model
facebook/omniASR-CTC-1B
Open
5
facebook/omniASR-CTC-300M
Open
3
facebook/omniASR-CTC-3B
Open
5
facebook/omniASR-LLM-1B
Open
5
facebook/omniASR-LLM-300M
Open
4
facebook/omniASR-LLM-3B
Open
4
facebook/omniASR-LLM-7B
Open
2
dsfsi/anv-whisper-large-v3-turbo-anv-zul
Open
4
dsfsi/anv-whisper-small-anv-zulu-first-batch
Open
6
openai/whisper-large-v3
Open
22
openai/whisper-small
Open
16
sitwala/whisper-large-anv-sot
Open
36
sitwala/whisper-large-v3-anv-sot
Open
40
sitwala/whisper-large-v3-turbo-anv-zul-150h
Open
4
sitwala/whisper-large-v3-turbo-anv-zul-250h
Open
4
sitwala/whisper-large-v3-turbo-anv-zul-50h
Open
4
What did the model get wrong?
facebook/omniASR-CTC-300M
Open
Example 5 of 100 · sample index 4
✅ What was actually said (isiZulu reference)
Ifundo
izoguqukela
kulwazi
lwe-'just-in-time'
phecelezi
ngesikhathi
esifanele.
Amathuba
azokuya
ngamandla
okuthola
ulwazi
ngesikhathi
esifanele
ngenhloso
efanele.
🤖 What this model heard
imfundo
izoguqukela
kulwazi
lwe
justintal
phecelezi
ngesikhathi
esifanele
amathuba
azokuya
ngamandla
okuthola
ulwazi
ngesikhathi
esifanele
ngenhloso
efanele
Correct
Wrong (different word)
Missed (skipped)
Extra (added)
14
Correct
2
Wrong
0
Missed
1
Extra
88%
Words right
0.312
WER
0.068
CER
16.97s
Duration
0.0s
Latency