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import os import pandas as pd # pip install numpy==1.19.3 from google.cloud import texttospeech # outdated or incomplete comparing to v1 from google.cloud import texttospeech_v1 os.environ['GOOGLE_APPLICATION_CREDENTIALS'] = r"GoogleCloudKey_MyServiceAcct.json" #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.name, voice.language_codes, 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( # https://cloud.google.com/text-to-speech/docs/reference/rpc/google.cloud.texttospeech.v1#audioencoding audio_encoding=texttospeech_v1.AudioEncoding.MP3 ) # 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. out.write(response.audio_content) print('Audio content written to file "output.mp3"')