Introduction to Google Cloud Text-to-Speech API - Text-to-Voice Conversion

The Google Cloud Text-to-Speech API is a machine learning service that allows developers to convert text into natural-sounding voice. In this guide, we'll explore the basics of the Google Cloud Text-to-Speech API and provide a sample Python code snippet for converting text into speech using the API.

Key Concepts

Before we dive into the code, let's understand some key concepts related to the Google Cloud Text-to-Speech API:

  • Text-to-Speech Conversion: The Text-to-Speech API converts text into lifelike speech, supporting multiple languages and voices.
  • Use Cases: It is used in applications like voice assistants, interactive voice response (IVR) systems, and audiobook narration.
  • Machine Learning Models: The API uses machine learning models to generate natural-sounding speech.

Sample Code: Converting Text to Speech

Here's a sample Python code snippet for converting text into speech using the Google Cloud Text-to-Speech API. To use this code, you need to set up a Google Cloud project and enable the Text-to-Speech API:

from import texttospeech
# Initialize the Text-to-Speech API client
client = texttospeech.TextToSpeechClient()
# Define the text to be converted to speech
text = "Hello, this is a sample text-to-speech conversion."
# Configure speech synthesis
input_text = texttospeech.SynthesisInput(text=text)
voice = texttospeech.VoiceSelectionParams(
audio_config = texttospeech.AudioConfig(
# Generate speech
response = client.synthesize_speech(
# Save the audio to a file
with open("output.wav", "wb") as out_file:
print("Speech synthesis complete.")

This code synthesizes the provided text and saves the generated speech to an audio file named "output.wav."


The Google Cloud Text-to-Speech API offers powerful text-to-voice conversion capabilities for applications. By integrating the API, you can make your applications more interactive with natural-sounding voice responses and narrations.