Dataset
Lwazi
ANV
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Model summary →
Model
facebook/omniASR-CTC-1B
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4
facebook/omniASR-CTC-300M
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5
facebook/omniASR-CTC-3B
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5
facebook/omniASR-CTC-7B
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5
facebook/omniASR-LLM-1B
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4
facebook/omniASR-LLM-300M
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3
facebook/omniASR-LLM-3B
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5
facebook/omniASR-LLM-7B
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4
aadel4/omniASR-CTC-1B-v2
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6
aadel4/omniASR-CTC-300M-v2
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4
badrex/w2v-bert-2.0-zulu-asr
Open
3
dsfsi/anv-whisper-large-v3-turbo-anv-zul
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3
dsfsi/anv-whisper-small-anv-zulu-first-batch
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6
facebook/mms-1b-all
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5
openai/whisper-large-v3
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6
openai/whisper-small
Open
7
sitwala/whisper-large-anv-sot
Open
5
sitwala/whisper-large-v3-anv-sot
Open
8
sitwala/whisper-large-v3-turbo-anv-zul-150h
Open
2
sitwala/whisper-large-v3-turbo-anv-zul-250h
Open
3
sitwala/whisper-large-v3-turbo-anv-zul-50h
Open
5
What did the model get wrong?
sitwala/whisper-large-anv-sot
Open
Example 82 of 100 · sample index 81
✅ What was actually said (isiZulu reference)
Mero-
Meromo,
mngane
wami,
asiziyeke
lezo.
🤖 What this model heard
mero
melommo
ranewame
ha
se
zihekeletso
Correct
Wrong (different word)
Missed (skipped)
Extra (added)
1
Correct
5
Wrong
0
Missed
0
Extra
17%
Words right
1.000
WER
0.452
CER
6.01s
Duration
0.1s
Latency