DatasetLwaziANV

← All examples Model summary →

Modelfacebook/omniASR-CTC-1BOpen8facebook/omniASR-CTC-300MOpen6facebook/omniASR-CTC-3BOpen8facebook/omniASR-CTC-7BOpen7facebook/omniASR-LLM-1BOpen7facebook/omniASR-LLM-300MOpen6facebook/omniASR-LLM-3BOpen7facebook/omniASR-LLM-7BOpen6aadel4/omniASR-CTC-1B-v2Open6aadel4/omniASR-CTC-300M-v2Open5badrex/w2v-bert-2.0-zulu-asrOpen5dsfsi/anv-whisper-large-v3-turbo-anv-zulOpen6dsfsi/anv-whisper-small-anv-zulu-first-batchOpen6facebook/mms-1b-allOpen5openai/whisper-large-v3Open6openai/whisper-smallOpen7sitwala/whisper-large-anv-sotOpen9sitwala/whisper-large-v3-anv-sotOpen16sitwala/whisper-large-v3-turbo-anv-zul-150hOpen7sitwala/whisper-large-v3-turbo-anv-zul-250hOpen6sitwala/whisper-large-v3-turbo-anv-zul-50hOpen6

What did the model get wrong?

badrex/w2v-bert-2.0-zulu-asrOpen   Example 76 of 100  ·  sample index 75

✅ What was actually said (isiZulu reference)
wamzondan-,wamzondanjalo-ke,uNatanau-Onyesha.
🤖 What this model heard
wamzodwanjalokeunatanau-onyendla
Correct
Wrong (different word)
Missed (skipped)
Extra (added)
1
Correct
4
Wrong
1
Missed
0
Extra
17%
Words right
0.833
WER
0.380
CER
6.52s
Duration
0.1s
Latency