DatasetLwaziANV

← All examples Model summary →

Modelfacebook/omniASR-CTC-1BOpen5facebook/omniASR-CTC-300MOpen8facebook/omniASR-CTC-3BOpen4facebook/omniASR-LLM-1BOpen3facebook/omniASR-LLM-300MOpen5facebook/omniASR-LLM-3BOpen2facebook/omniASR-LLM-7BOpen2dsfsi/anv-whisper-large-v3-turbo-anv-zulOpen8dsfsi/anv-whisper-small-anv-zulu-first-batchOpen9openai/whisper-large-v3Open32openai/whisper-smallOpen64sitwala/whisper-large-anv-sotOpen58sitwala/whisper-large-v3-anv-sotOpen56sitwala/whisper-large-v3-turbo-anv-zul-150hOpen10sitwala/whisper-large-v3-turbo-anv-zul-250hOpen12sitwala/whisper-large-v3-turbo-anv-zul-50hOpen9

What did the model get wrong?

dsfsi/anv-whisper-small-anv-zulu-first-batchOpen   Example 22 of 100  ·  sample index 21

✅ What was actually said (isiZulu reference)
Elawini,ikhabethelohlobolwengibelisetshenziselwaukubekaizimpahlazokugqokakanyenezinyeizintoongahleuzidinge.Izinguboziyafakwafuthinakwishalofu.Ngokujwayelekile,izinguboezinhlezihlalakwingibelaphoziphanyekwakhonangesiphanyeka,kuthiezokuhlalaekhayazonazihlaleemashalofini.
🤖 What this model heard
elawiniikhabethelohlobolwengibelisetshenziselwaukubhekaizimpahlazokugqokakanyenezinyeizintoongahleuzidiniizinguboziyafakwafuthinakwishalofingokujwayelekileizinguboezinhlezihlalakwingibelaphoziphanyekwakhonangesiphanyeka
Correct
Wrong (different word)
Missed (skipped)
Extra (added)
23
Correct
3
Wrong
6
Missed
0
Extra
72%
Words right
0.375
WER
0.200
CER
38.75s
Duration
0.1s
Latency