Dataset
Lwazi
ANV
← All examples
Model summary →
Model
facebook/omniASR-CTC-1B
Open
5
facebook/omniASR-CTC-300M
Open
7
facebook/omniASR-CTC-3B
Open
4
facebook/omniASR-LLM-1B
Open
8
facebook/omniASR-LLM-300M
Open
10
facebook/omniASR-LLM-3B
Open
7
facebook/omniASR-LLM-7B
Open
5
dsfsi/anv-whisper-large-v3-turbo-anv-zul
Open
5
dsfsi/anv-whisper-small-anv-zulu-first-batch
Open
11
openai/whisper-large-v3
Open
29
openai/whisper-small
Open
29
sitwala/whisper-large-anv-sot
Open
31
sitwala/whisper-large-v3-anv-sot
Open
30
sitwala/whisper-large-v3-turbo-anv-zul-150h
Open
5
sitwala/whisper-large-v3-turbo-anv-zul-250h
Open
6
sitwala/whisper-large-v3-turbo-anv-zul-50h
Open
8
What did the model get wrong?
sitwala/whisper-large-anv-sot
Open
Example 8 of 100 · sample index 7
✅ What was actually said (isiZulu reference)
ULouw
Steytler,
Usihlalo
we-Grain
SA,
waxoxa
ngokuhlangana
ekulimeni,
washo
futhi
ukuthi
ukusebenzisana
kuyisikhiye
sokuphumelela
kulo
msebenzi
wokulima.
🤖 What this model heard
o
low
state
la
ho
sehlalohwe
crane
sa
wa
qotang
ho
qlangana
ekelemeni
wash
of
40
ho
kothee
ho
ke
sebense
sana
ko
eskeye
so
ho
phomelela
kolong
sebense
ho
ke
leng
Correct
Wrong (different word)
Missed (skipped)
Extra (added)
1
Correct
16
Wrong
0
Missed
15
Extra
6%
Words right
1.882
WER
0.484
CER
16.24s
Duration
0.3s
Latency