Automatic Speech Recognition
NeMo
ONNX
GGUF
parakeet
tdt
sherpa-onnx
multilingual
speech-recognition
gabor
fastconformer
Instructions to use aoiandroid/orukeet with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- NeMo
How to use aoiandroid/orukeet with NeMo:
import nemo.collections.asr as nemo_asr asr_model = nemo_asr.models.ASRModel.from_pretrained("aoiandroid/orukeet") transcriptions = asr_model.transcribe(["file.wav"]) - Notebooks
- Google Colab
- Kaggle
File size: 848 Bytes
88287a0 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 | """Use an installation receipt without downloading anything during transcription."""
import argparse
import json
import sys
from pathlib import Path
from orukeet import Orukeet
def main():
if hasattr(sys.stdout, "reconfigure"):
sys.stdout.reconfigure(encoding="utf-8")
parser = argparse.ArgumentParser(description=__doc__)
parser.add_argument('audio', type=Path, nargs='+')
parser.add_argument('--installation', type=Path, default=Path('installation.json'))
args = parser.parse_args()
config = json.loads(args.installation.read_text(encoding='utf-8-sig'))
with Orukeet(config['model'], config['runtime'], device=config['device']) as model:
for path in args.audio:
print(json.dumps({'file': str(path), **model.transcribe(path)}, ensure_ascii=False))
if __name__ == '__main__':
main()
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