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Source Code:  

import os
import pandas as pd #  pip install numpy==1.19.3
from import texttospeech # outdated or incomplete comparing to v1
from import texttospeech_v1

os.environ['GOOGLE_APPLICATION_CREDENTIALS'] = r"GoogleCloudKey_MyServiceAcct.json"

# Instantiates a client
client = texttospeech_v1.TextToSpeechClient()

voice_list = []
for voice in client.list_voices().voices:
    voice_list.append([, voice.language_codes[0], voice.ssml_gender, voice.natural_sample_rate_hertz])
df_voice_list = pd.DataFrame(voice_list, columns=['name', 'language code', 'ssml gender', 'hertz rate']).to_csv('Voice List.csv', index=False)

# Set the text input to be synthesized
quote = 'The habit of saving is itself an education; it fosters every virtue, teaches self-denial, cultivates the sense of order, trains to forethought, and so broadens the mind. By T.T.Munger'
synthesis_input = texttospeech_v1.SynthesisInput(text=quote)

voice = texttospeech_v1.VoiceSelectionParams(
    language_code="en-in", ssml_gender=texttospeech.SsmlVoiceGender.NEUTRAL

voice = texttospeech_v1.VoiceSelectionParams(
    name='ar-XA-Wavenet-B', language_code="en-GB"
    # name='vi-VN-Wavenet-D', language_code="vi-VN"

# Select the type of audio file you want returned
audio_config = texttospeech_v1.AudioConfig(

# Perform the text-to-speech request on the text input with the selected
# voice parameters and audio file type
response = client.synthesize_speech(
    input=synthesis_input, voice=voice, audio_config=audio_config

# The response's audio_content is binary.
with open(r"H:\PythonVenv\GoogleAI\TextToSpeech\output2.mp3", "wb") as out:
    # Write the response to the output file.
    print('Audio content written to file "output.mp3"')