#!/usr/bin/env python3
from vosk import Model, KaldiRecognizer, SetLogLevel
import sys
import os
import wave
import subprocess
import base64
SetLogLevel(0)
# if not os.path.exists("models/model-fa"):
# print ("Please download the model from https://alphacephei.com/vosk/models and unpack as 'model' in the current folder.")
# exit (1)
sample_rate=16000
dirname = os.path.dirname(__file__)
filename = os.path.join(dirname, 'models/model-fa')
model = Model(filename)
rec = KaldiRecognizer(model, sample_rate)
process = subprocess.Popen(['ffmpeg', '-loglevel', 'quiet', '-i',
sys.argv[1],
'-ar', str(sample_rate) , '-ac', '1', '-f', 's16le', '-'],
stdout=subprocess.PIPE)
while True:
data = process.stdout.read(4000)
if len(data) == 0:
break
rec.AcceptWaveform(data)
# if rec.AcceptWaveform(data):
# print(rec.Result())
# else:
# print(rec.PartialResult())
result = rec.FinalResult()
print(result)