Python voice recognition using vosk for Turkish language

main.py

import os
import wave
from vosk import Model, KaldiRecognizer
import json
import librosa
import soundfile as sf

def get_text_from_voice(filename):

    if not os.path.exists("model"):
        print ("Please download the model from https://alphacephei.com/vosk/models and unpack as 'model' in the current folder.")
        exit (1)

    x,_ = librosa.load(filename, sr=16000)
    sf.write('tmp.wav', x, 16000)
    wf = wave.open('tmp.wav', "rb")
    if wf.getnchannels() != 1 or wf.getsampwidth() != 2 or wf.getcomptype() != "NONE":
        print ("Audio file must be WAV format mono PCM.")
        exit (1)

    model = Model("model")
    rec = KaldiRecognizer(model, wf.getframerate())
    rec.SetWords(True)

    text_lst =[]
    p_text_lst = []
    p_str = []
    len_p_str = []
    txt = [""]
    id = 0
    while True:
        data = wf.readframes(4000)
        if len(data) == 0:
            break
        if rec.AcceptWaveform(data):
            text_lst.append(rec.Result())
            print(rec.Result())
            id += 1
            txt.append("")
        else:
            p_text_lst.append(rec.PartialResult())
            p = json.loads(rec.PartialResult())["partial"]
            txt[id] = p
            # print(p)

    if len(text_lst) !=0:
        jd = json.loads(text_lst[0])
        txt_str = jd["text"]
        
    elif len(p_text_lst) !=0: 
        for i in range(0,len(p_text_lst)):
            temp_txt_dict = json.loads(p_text_lst[i])
            p_str.append(temp_txt_dict['partial'])
       
        len_p_str = [len(p_str[j]) for j in range(0,len(p_str))]
        max_val = max(len_p_str)
        indx = len_p_str.index(max_val)
        txt_str = p_str[indx]
        print(txt_str)
        txt.append(txt_str)
            
    else:
        txt_str =''

    return ". ".join(txt)

res = get_text_from_voice("test.ogg")
print(res)