Automatic Speech Recognition
NeMo
PyTorch
Belarusian
speech
audio
Transducer
Conformer
Transformer
NeMo
hf-asr-leaderboard
Eval Results (legacy)
Instructions to use nvidia/stt_be_conformer_transducer_large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- NeMo
How to use nvidia/stt_be_conformer_transducer_large with NeMo:
import nemo.collections.asr as nemo_asr asr_model = nemo_asr.models.ASRModel.from_pretrained("nvidia/stt_be_conformer_transducer_large") transcriptions = asr_model.transcribe(["file.wav"]) - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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import nemo.collections.asr as nemo_asr
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asr_model = nemo_asr.models.EncDecRNNTBPEModel.from_pretrained("nvidia/stt_be_conformer_transducer_large")
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```
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### Transcribing many audio files
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```shell
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import nemo.collections.asr as nemo_asr
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asr_model = nemo_asr.models.EncDecRNNTBPEModel.from_pretrained("nvidia/stt_be_conformer_transducer_large")
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```
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### Transcribing using Python
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First, let's get a sample
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```
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wget https://dldata-public.s3.us-east-2.amazonaws.com/2086-149220-0033.wav
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```
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Then simply do:
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```
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output = asr_model.transcribe(['2086-149220-0033.wav'])
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print(output[0].text)
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```
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### Transcribing many audio files
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```shell
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