vosk-api | Offline speech recognition API for Android iOS | Speech library

pcm = recorder.read() 
result = porcupine.process(pcm)

sp = struct.pack("h" * len(pcm), *pcm)

if self.rec.AcceptWaveform(sp):
    res = json.loads(self.rec.Result())
    if res["text"] != "

filtered_list = []

for w in words:
    already_seen = False
    for seen in filtered_list:
        # print(seen.word)
        if w.compare(seen):
            already_seen = True
    if not already_seen:
        filtered_list.append(w)

# 

frequency = {}

for w in words:
    if frequency.get(w.word, False):
        frequency[w.word].append(w)
    else:
        frequency[w.word] = [w]

repeated_words_list = []
for key in frequency:
    if len(frequency[key]) > 1:
        r

import sys
import os
import subprocess
import json
import math

# tested with VOSK 0.3.15
import vosk
import librosa
import numpy
import pandas



def extract_words(res):
   jres = json.loads(res)
   if not 'result' in jres:
       return

from vosk import Model, KaldiRecognizer
import os

if not os.path.exists("model-en"):
    print ("Please download the model from https://github.com/alphacep/vosk-android-demo/releases and unpack as 'model-en' in the current folder.")
    e

###############################################################################################
######## STT SPEECH TO TEXT FUNCTION THAT RETURNS THE VARIABLE: command
import pyaudio
from vosk import Model, KaldiRecognizer

def myCommand()

#!/usr/bin/python3

from vosk import Model, KaldiRecognizer
import sys
import os
import wave

if not os.path.exists("model-en"):
    print ("Please download the model from https://github.com/alphacep/kaldi-android-demo/releases and unpack 

#!/usr/bin/python3

from vosk import Model, KaldiRecognizer, SpkModel
import sys
import wave
import json
import os
import numpy as np

model_path = "model-en"
spk_model_path = "model-spk"

if not os.path.exists(model_path):
    print ("Ple