Dataset
Lwazi
ANV
← All examples
Model summary →
Model
facebook/omniASR-CTC-1B
Open
6
facebook/omniASR-CTC-300M
Open
6
facebook/omniASR-CTC-3B
Open
4
facebook/omniASR-LLM-1B
Open
3
facebook/omniASR-LLM-300M
Open
3
facebook/omniASR-LLM-3B
Open
2
facebook/omniASR-LLM-7B
Open
1
dsfsi/anv-whisper-large-v3-turbo-anv-zul
Open
3
dsfsi/anv-whisper-small-anv-zulu-first-batch
Open
6
openai/whisper-large-v3
Open
26
openai/whisper-small
Open
40
sitwala/whisper-large-anv-sot
Open
47
sitwala/whisper-large-v3-anv-sot
Open
52
sitwala/whisper-large-v3-turbo-anv-zul-150h
Open
2
sitwala/whisper-large-v3-turbo-anv-zul-250h
Open
4
sitwala/whisper-large-v3-turbo-anv-zul-50h
Open
7
What did the model get wrong?
facebook/omniASR-LLM-300M
Open
Example 37 of 100 · sample index 36
✅ What was actually said (isiZulu reference)
Yize
kungebona
bonke
abesilisa
abakhuluphele
kakhulu
abanesimo
sowesilisa
esingcwatshiwe,
abesilisa
abangama-87
percent
abathole
ukwelashwa
ngokuhlinzwa
kwepipi
elingcwatshiwe
babikwa
ukuthi
bakhuluphele.
🤖 What this model heard
yize
kungebona
bonke
abesilisa
abakhuluphele
kakhulu
abanisimo
sowesilisa
esingcwatshiwe
abesilisa
abangama
abathole
ukwelashwa
ngokuhlinzwa
kwepipi
elingcwatshiwe
babikwa
ukuthi
bakhuluphele
Correct
Wrong (different word)
Missed (skipped)
Extra (added)
17
Correct
2
Wrong
1
Missed
0
Extra
85%
Words right
0.250
WER
0.069
CER
23.63s
Duration
2.6s
Latency