Digisensus/lithuanian-phone-speech-liepa-3-429h-punctuated
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How to use Digisensus/parakeet-tdt-0.6b-lt-study-s with NeMo:
import nemo.collections.asr as nemo_asr
asr_model = nemo_asr.models.ASRModel.from_pretrained("Digisensus/parakeet-tdt-0.6b-lt-study-s")
transcriptions = asr_model.transcribe(["file.wav"])Research checkpoint from the study Lithuanian speech recognition: effects of dialect training and
transcript spelling. Fine-tuned from nvidia/parakeet-tdt-0.6b-v3 on LIEPA-3 telephone speech (420.17 h).
Output is lowercase spoken form without punctuation. This is a study model, not a product model.
| Test | WER |
|---|---|
| Dialect test, dialect-spelling reference | 42.11 |
| Dialect test, standard-spelling reference | 36.40 |
| Dialect test, either spelling accepted | 34.83 |
| LIEPA-3 telephone test | 10.76 |
| FLEURS lt test | 28.62 |
| Common Voice 19 lt test | 35.20 |
import nemo.collections.asr as nemo_asr
model = nemo_asr.models.ASRModel.from_pretrained("Digisensus/parakeet-tdt-0.6b-lt-study-s")
print(model.transcribe(["audio.wav"])[0].text)
| Run | ltd26/S/s1/a2 |
| Recipe | S (recipes/S.json in the code repo) |
| Splits | splits-v1 |
| Training | 10,000 updates, 192 clips per update, last checkpoint; full spec in config.json |
| Scorer | see registry/scores.csv in the code repo |
Base model
nvidia/parakeet-tdt-0.6b-v3