Instructions to use espnet/marathi_lrec2020 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ESPnet
How to use espnet/marathi_lrec2020 with ESPnet:
import soundfile from espnet2.bin.asr_inference import Speech2Text model = Speech2Text.from_pretrained( "espnet/marathi_lrec2020" ) speech, rate = soundfile.read("speech.wav") text, *_ = model(speech)[0] - Notebooks
- Google Colab
- Kaggle
Commit History
5 days ago
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Ship the scored epoch-60 ASR checkpoint and the character LM
Verified signatureThe previous upload held valid.loss.ave_10best.pth, which was never scored; every reported number came from the epoch-60 checkpoint (latest.pth), now shipped as 60epoch.pth. Adds the character LSTM LM used for the lm_weight 0.3 results, sets the usage example to the reported decoding settings, and replaces the dataset citation with the corpus paper (Abraham et al., LREC 2020). Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>c5268ee
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Update model
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