47 lines
1.4 KiB
Python
Executable File
47 lines
1.4 KiB
Python
Executable File
#!/usr/bin/env python3
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from vosk import Model, KaldiRecognizer, SetLogLevel
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import sys
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import json
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import os
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import wave
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import subprocess
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SetLogLevel(0)
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modelBase = os.getenv('VOSK_MODELS', os.path.join(os.getenv('XDG_DATA_HOME', os.environ['HOME']), 'vosk/models'))
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modelPath = os.path.join(modelBase, sys.argv[2] if len(sys.argv) > 2 else 'daanzu')
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if not os.path.exists(modelPath):
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print (f"Please download a model from https://alphacephei.com/vosk/models and unpack it to {modelPath}.", file=sys.stderr)
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exit (1)
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if len(sys.argv) < 2:
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print (f"Usage: {sys.argv[0]} <audio> [model]", file=sys.stderr)
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exit (1)
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sample_rate=16000
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model = Model(modelPath)
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kaldi = KaldiRecognizer(model, sample_rate)
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process = subprocess.Popen(['ffmpeg', '-loglevel', 'quiet', '-i',
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sys.argv[1],
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'-ar', str(sample_rate) , '-ac', '1', '-f', 's16le', '-'],
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stdout=subprocess.PIPE)
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def getText(result):
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res = json.loads(result)
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if not 'result' in res:
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return res['text']
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sec = res['result'][0]['start']
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time = "%02d:%02d" % (sec // 60, sec % 60)
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return "%s %s" % (time, res['text'])
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while True:
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data = process.stdout.read(4000)
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if len(data) == 0:
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break
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if kaldi.AcceptWaveform(data):
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print(getText(kaldi.Result()))
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print(getText(kaldi.FinalResult()))
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