nemo_asr.py

import aiofiles
import nemo
import nemo.collections.asr as nemo_asr


def transcribe(file, modelName="stt_rw_conformer_transducer_large"):
  with open(open.filename, 'rb') as out_file:
    out_file = file.read()  # async read
    #out_file.write(content)  # async write
    print(out_file.name)
  asr_model = nemo_asr.models.EncDecRNNTBPEModel.from_pretrained(
                model_name=modelName)
  if not file.name.endswith("wav"):
    sound = AudioSegment.from_mp3(out_file.name)
    sound.export(out_file.name, format="wav")
    files = [out_file.name]
  pac.convert_wav_to_16bit_mono(out_file.name,out_file.name)
    # print("file loaded is **************",file.file)
  for fname, transcription in zip(files, asr_model.transcribe(paths2audio_files=files)):
    print(f"Audio in {fname} was recognized as: {transcription}")
    print(transcription[0])
    return {"text": transcription[0], "filename": file.filename}