#!/usr/bin/env python3

from vosk import Model, KaldiRecognizer, SetLogLevel
import sys
import json
import os
import wave
import subprocess

SetLogLevel(0)

modelBase = '/home/janek/data/projects/_forks/vosk-api/python/example/models'
modelPath = os.path.join(modelBase, sys.argv[2] if len(sys.argv) > 2 else 'daanzu')
if not os.path.exists(modelPath):
    print (f"Please download a model from https://alphacephei.com/vosk/models and unpack it to {modelPath}.", file=sys.stderr)
    exit (1)

sample_rate=16000
model = Model(modelPath)
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
    if rec.AcceptWaveform(data):
        res = json.loads(rec.Result())
        print (res['text'])

res = json.loads(rec.FinalResult())
print (res['text'])