53 lines
1.1 KiB
Python
53 lines
1.1 KiB
Python
from transcription.engines.BaseEngine import BaseEngine
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import wave, json
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from vosk import Model, KaldiRecognizer
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"""
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import wave
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import json
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import sys
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from multiprocessing.dummy import Pool
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from vosk import Model, KaldiRecognizer
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model = Model("en-us")
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def recognize(line):
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uid, fn = line.split()
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wf = wave.open(fn, "rb")
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rec = KaldiRecognizer(model, wf.getframerate())
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text = ""
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while True:
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data = wf.readframes(1000)
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if len(data) == 0:
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break
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if rec.AcceptWaveform(data):
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jres = json.loads(rec.Result())
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text = text + " " + jres["text"]
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jres = json.loads(rec.FinalResult())
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text = text + " " + jres["text"]
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return uid + text
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def main():
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p = Pool(8)
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texts = p.map(recognize, open(sys.argv[1], encoding="utf-8").readlines())
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print ("\n".join(texts))
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main()
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"""
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class VoskEngine(BaseEngine):
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TARGET_SAMPLING_RATE = 16000
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def loadModel(self) -> None:
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...
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def unloadModel(self) -> None:
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...
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def transcribeBatch(
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self,
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batch,
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) -> str:
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... |