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Source Code:
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from google.cloud import texttospeech # outdated or incomplete comparing to v1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[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(
# 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"')
