Google ships its most expressive Gemini 3.1 text-to-speech model yet with 70+ language support

Learn how to use Google's new Gemini 3.1 Flash Text-to-Speech model to convert text into natural-sounding speech in over 70 languages with precise control over style, pace, and tone.

Introduction

In this tutorial, you'll learn how to use Google's new Gemini 3.1 Flash Text-to-Speech model to convert text into natural-sounding speech in over 70 languages. This technology allows you to create expressive audio content with precise control over style, pace, and tone. Whether you're building an educational app, accessibility tool, or content creator, this tutorial will guide you through setting up and using this powerful text-to-speech capability.

Prerequisites

Before starting this tutorial, you'll need:

A Google Cloud account with billing enabled
Basic understanding of Python programming
Python 3.7 or higher installed on your computer
Google Cloud SDK installed and configured

Step-by-Step Instructions

Step 1: Set Up Your Google Cloud Project

1.1 Create a new Google Cloud project

First, navigate to the Google Cloud Console and create a new project. Give it a descriptive name like "Gemini-TTS-Project". This project will host all your text-to-speech resources.

1.2 Enable the Text-to-Speech API

Once your project is created, go to the API Library and search for "Text-to-Speech". Click on the Text-to-Speech API and enable it for your project. This step is crucial as it grants your application access to the Gemini TTS capabilities.

1.3 Create a service account and download credentials

Navigate to the IAM & Admin section and create a new service account. Download the JSON key file and save it securely. This file will authenticate your application when making requests to Google's TTS service.

Step 2: Install Required Dependencies

2.1 Install the Google Cloud Text-to-Speech client library

Open your terminal or command prompt and run the following command to install the required Python library:

pip install google-cloud-texttospeech

This library provides the Python interface to interact with Google's text-to-speech service, including the new Gemini 3.1 Flash TTS model.

2.2 Set up environment variables

Set the environment variable to point to your service account key file:

export GOOGLE_APPLICATION_CREDENTIALS="path/to/your/service-account-key.json"

This tells the Google Cloud client libraries where to find your authentication credentials.

Step 3: Create Your First Text-to-Speech Application

3.1 Write the basic Python script

Create a new Python file called gemini_tts.py and start with this basic structure:

from google.cloud import texttospeech
import os

# Initialize the client
client = texttospeech.TextToSpeechClient()

# Configure the synthesis input
input_text = texttospeech.SynthesisInput(text="Hello, welcome to the world of Gemini text-to-speech technology!")

# Configure the voice parameters
voice = texttospeech.VoiceSelectionParams(
    language_code="en-US",
    name="en-US-Neural2-J",
    ssml_gender=texttospeech.SsmlVoiceGender.MALE
)

# Configure the audio output
audio_config = texttospeech.AudioConfig(
    audio_encoding=texttospeech.AudioEncoding.MP3,
    speaking_rate=1.0,
    pitch=0.0,
    volume_gain_db=0.0
)

# Perform the text-to-speech request
response = client.synthesize_speech(
    input=input_text,
    voice=voice,
    audio_config=audio_config
)

# Write the audio content to a file
with open("output.mp3", "wb") as out:
    out.write(response.audio_content)
    print('Audio content written to file "output.mp3"')

This script demonstrates the basic workflow: initialize the client, configure input text, select a voice, set audio parameters, and generate the audio file.

3.2 Run your first test

Execute your script with:

python gemini_tts.py

You should see an output.mp3 file in your directory. Play it to hear the synthesized speech in English.

Step 4: Explore Multi-Language Support

4.1 Test different languages

Modify your script to test various languages supported by Gemini 3.1. Try this example:

language_codes = ["en-US", "es-ES", "fr-FR", "de-DE", "ja-JP"]

for lang in language_codes:
    input_text = texttospeech.SynthesisInput(text="Hello, this is a test in " + lang)
    voice = texttospeech.VoiceSelectionParams(
        language_code=lang,
        name=None,  # Let Google choose the best voice
        ssml_gender=texttospeech.SsmlVoiceGender.NEUTRAL
    )
    
    audio_config = texttospeech.AudioConfig(
        audio_encoding=texttospeech.AudioEncoding.MP3
    )
    
    response = client.synthesize_speech(
        input=input_text,
        voice=voice,
        audio_config=audio_config
    )
    
    with open(f"output_{lang}.mp3", "wb") as out:
        out.write(response.audio_content)
        print(f'Audio content written to file "output_{lang}.mp3"')

This code will generate audio files in multiple languages, showcasing the 70+ language support of Gemini 3.1 Flash TTS.

4.2 Adjust speech parameters

Experiment with different speaking rates and pitches to create more expressive audio:

# Test different speaking rates
rates = [0.5, 1.0, 1.5, 2.0]

for rate in rates:
    audio_config = texttospeech.AudioConfig(
        audio_encoding=texttospeech.AudioEncoding.MP3,
        speaking_rate=rate,
        pitch=0.0
    )
    
    response = client.synthesize_speech(
        input=input_text,
        voice=voice,
        audio_config=audio_config
    )
    
    with open(f"output_rate_{rate}.mp3", "wb") as out:
        out.write(response.audio_content)
        print(f'Audio content written to file "output_rate_{rate}.mp3"')

Adjusting these parameters allows you to control the naturalness and expressiveness of the generated speech.

Step 5: Advanced Features and Audio Tags

5.1 Use SSML for advanced control

For more precise control over speech characteristics, use Speech Synthesis Markup Language (SSML). Here's an example:

ssml_text = "This is a very important announcement.  Please listen carefully."

input_text = texttospeech.SynthesisInput(ssml=ssml_text)

# Configure voice for more expressive speech
voice = texttospeech.VoiceSelectionParams(
    language_code="en-US",
    name="en-US-Neural2-J",
    ssml_gender=texttospeech.SsmlVoiceGender.MALE
)

audio_config = texttospeech.AudioConfig(
    audio_encoding=texttospeech.AudioEncoding.MP3,
    speaking_rate=1.2,
    pitch=1.0
)

response = client.synthesize_speech(
    input=input_text,
    voice=voice,
    audio_config=audio_config
)

with open("ssml_output.mp3", "wb") as out:
    out.write(response.audio_content)
    print('SSML audio content written to file "ssml_output.mp3"')

SSML allows you to add emphasis, breaks, and other audio effects that enhance the naturalness of speech.

5.2 Implement error handling

Add error handling to make your application more robust:

try:
    response = client.synthesize_speech(
        input=input_text,
        voice=voice,
        audio_config=audio_config
    )
    
    with open("output.mp3", "wb") as out:
        out.write(response.audio_content)
        print('Audio content written to file "output.mp3"')
        
except Exception as e:
    print(f'Error occurred: {e}')

This ensures your application gracefully handles any issues that might occur during text-to-speech conversion.

Summary

In this tutorial, you've learned how to set up and use Google's Gemini 3.1 Flash Text-to-Speech model to convert text into natural-sounding speech in over 70 languages. You've explored basic usage, multi-language support, speech parameter control, SSML for advanced features, and error handling. This powerful technology opens up numerous possibilities for creating accessible content, educational applications, and voice-enabled services. With the ability to control style, pace, and tone through audio tags, you can create highly expressive and engaging audio content that enhances user experience across multiple languages and applications.