DatasetLwaziANV

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Modelfacebook/omniASR-CTC-1BOpen7facebook/omniASR-CTC-300MOpen9facebook/omniASR-CTC-3BOpen7facebook/omniASR-CTC-7BOpen8facebook/omniASR-LLM-1BOpen8facebook/omniASR-LLM-300MOpen10facebook/omniASR-LLM-3BOpen7facebook/omniASR-LLM-7BOpen10aadel4/omniASR-CTC-1B-v2Open13aadel4/omniASR-CTC-300M-v2Open13badrex/w2v-bert-2.0-zulu-asrOpen9dsfsi/anv-whisper-large-v3-turbo-anv-zulOpen13dsfsi/anv-whisper-small-anv-zulu-first-batchOpen13facebook/mms-1b-allOpen11openai/whisper-large-v3Open13openai/whisper-smallOpen222sitwala/whisper-large-anv-sotOpen13sitwala/whisper-large-v3-anv-sotOpen13sitwala/whisper-large-v3-turbo-anv-zul-150hOpen9sitwala/whisper-large-v3-turbo-anv-zul-250hOpen6sitwala/whisper-large-v3-turbo-anv-zul-50hOpen8

What did the model get wrong?

facebook/omniASR-LLM-3BOpen   Example 65 of 100  ·  sample index 64

✅ What was actually said (isiZulu reference)
[s]kunye,chashazakunye,chashazakunye,[n]na-[um][n]whatisna.
🤖 What this model heard
wa-kunyeqhashazakunyeqhashazakunyena-ehhewhatisnight
Correct
Wrong (different word)
Missed (skipped)
Extra (added)
6
Correct
5
Wrong
2
Missed
0
Extra
46%
Words right
0.800
WER
0.288
CER
9.14s
Duration
0.3s
Latency