Build Human-Like AI Voice App with Gemini 3.1 Flash TTS

AI voice era has a significant drawback. It really works like a robotic, studying a script phrase by phrase, with no emotions or feelings. It could be intelligent, however it issues much less if there isn’t a human feeling hooked up to it. The best way the AI generates its voice makes it exhausting to really feel such as you’re having a considerable dialog.

This all modified with Google DeepMind releasing the Gemini 3.1 Flash TTS on April 15, 2026. This TTS isn’t just a complicated speech synthesizer, however it additionally now features as an AI speech director!

This know-how means that you can create a voice actor studio with none actual tools, just by utilizing an API name or in Google Studio. Now, allow us to take a look at the brand new options of this know-how, what it means to you, and most significantly, three real-world tasks you can create and use instantly with it!

What Makes Gemini 3.1 Flash TTS Totally different?

In earlier variations of AI TTS, the one possibility for you was primary voice and pace management. The Gemini 3.1 Flash TTS is a major enhancement over earlier generations and offers a bunch of latest options.

The brand new options accessible with Gemini 3.1 Flash TTS embrace:

Audio Tags: Add Pure Language “Stage Instructions” into your transcript. For instance, telling the mannequin to sound like they’re excited, to whisper a secret, or to pause earlier than persevering with will consequence within the mannequin performing as requested.

Scene Instructions: Outline the Environmental and Narrative context for the complete script, guaranteeing that characters stay in character for a number of successive dialogue items routinely.

Character Profiles: Set up distinctive, up-to-date audio profiles for every character. Apply your Director’s Notes to set the supply of every character’s Audio Profile with respect to: Tempo, Tone and Accent.

Inline Pivot Tags: Audio system can quickly change from Regular to Panicked with out the necessity for a separate API name, even when it’s halfway by way of a dialogue.

Exportable Settings: As soon as the voice has been configured, export the precise configuration to the Gemini API code for fast use.

Each audio file created with Gemini 3.1 is embedded with “SynthID”, an invisible audio signature developed by Google DeepMind to assist observe the utilization of artificial audio recordsdata. It mainly offers a technique of detecting artificial audio from historically produced audio recordsdata.

Getting Began with Gemini 3.1 Flash TTS

The Gemini 3.1 Flash TTS has three accessible accessible platforms presently:

Developer customers can preview by way of Gemini’s API and the Google AI Studio

Enterprise customers can preview by way of Vertex AI

Google Vids is accessible to Workspace customers solely

For the 2 examples that make the most of API know-how under, please make sure you get a free Gemini API Key to make use of by visiting aistudio.google.com. The third instance would require only a net browser to entry.

App 1: Construct an Emotional Audiobook Narrator utilizing Gemini API

In our real-world take a look at of the Gemini 3.1 Flash TTS, we will construct a Python program for changing plain textual content tales to audiobooks with distinct sounds of emotion utilizing audio tags. That is how audio tags can drastically enhance the standard of the TTS audio within the audiobook course of. Audiobook TTS typically has a monotonous tone; nevertheless, whenever you management the feelings by way of the audio tags per scene, there ought to be a noticeable distinction within the audio output.

Directions:

1. Set up the Gemini Python SDK:

pip set up google-generativeai

2. Create a file named audiobook.py and paste within the following code:

import google.generativeai as genai
import base64
genai.configure(api_key=”YOUR_API_KEY”)
story = “””
[calm, slow, hushed narrator voice]
The previous home had been empty for thirty years.
[building tension, slight tremor in voice]
As she pushed open the door, the floorboards groaned beneath her.
[sharp, alarmed, fast-paced]
Then she noticed it. A shadow. Transferring towards her.
[relieved exhale, warm and soft]
It was simply the cat. An previous tabby, blinking up at her in the dead of night.
“””
consumer = genai.Consumer()
response = consumer.fashions.generate_content(
mannequin=”gemini-3.1-flash-tts-preview”,
contents=story,
config={
“response_modalities”: [“AUDIO”],
“speech_config”: {
“voice_config”: {
“prebuilt_voice_config”: {“voice_name”: “Kore”}
}
}
}
)
audio_data = response.candidates[0].content material.components[0].inline_data.information
wav_bytes = base64.b64decode(audio_data)
with open(“audiobook_output.wav”, “wb”) as f:
f.write(wav_bytes)
print(“Saved: audiobook_output.wav”)

3. Exchange the placeholder of “YOUR_API_KEY” with your individual API KEY and run this system

python audiobook.py

4. Open and take heed to the audio file situated at audiobook_output.wav

The stage instructions present in brackets will point out how the narrator ought to emotionally interpret every chapter of an audiobook. For instance, by studying every chapter, the narrator will go from a peaceful whisper to confusion and panic, adopted by a peaceful aid in a single steady audio recording.

Output:

Enhance it additional: Discover any chapter from the Challenge Gutenberg website and use it within the audiobook; then loop by way of the paragraph in a chapter. You can too tag the sentiment for every paragraph utilizing the sentiment audio tags to create your individual audiobooks. By this technique, it’s best to have the ability to create an immediate and expressive audiobook with little or no studio time required.

App 2: Multi-Character Podcast Generator utilizing Gemini API

On this test-case, we are going to use the multi-speaker/host function of Gemini 3.1 Flash Textual content-to-Speech. For this, we are going to construct a podcast script with two voices (two separate speeds, tones, and attitudes) from one single API name throughout the identical audio file.

Apparently, there isn’t a want to attach 2 API calls, and there’s no want for post-production for this. Simply present a single immediate that can convert to 2 separate personalities right into a single audio file.

Directions:

1. Create a script known as podcast_gen.py

import google.generativeai as genai
import base64
genai.configure(api_key=”YOUR_API_KEY”)
transcript = “””

Two tech journalists debate whether or not AI voice is overhyped.
Alex is skeptical and speaks shortly with a dry tone.
Jordan is enthusiastic, heat, and barely quicker when excited.

Yearly somebody declares that is the AI voice breakthrough.
And yearly, the demos sound nice however actual adoption drags.

However this time the numbers again it up. We’re not speaking demos —
we’re speaking manufacturing deployments delivery precise product.

Deployments of chatbots that also mispronounce “Worcestershire.”
Unbelievable milestone.

Okay, honest. However the trajectory — you genuinely can’t argue
with the place that is heading in twelve months.

“””
consumer = genai.Consumer()
response = consumer.fashions.generate_content(
mannequin=”gemini-3.1-flash-tts-preview”,
contents=transcript,
config={
“response_modalities”: [“AUDIO”],
“speech_config”: {
“multi_speaker_voice_config”: {
“speaker_voice_configs”: [
{
“speaker”: “Alex”,
“voice_config”: {
“prebuilt_voice_config”: {“voice_name”: “Fenrir”}
}
},
{
“speaker”: “Jordan”,
“voice_config”: {
“prebuilt_voice_config”: {“voice_name”: “Aoede”}
}
}
]
}
}
}
)
audio_data = response.candidates[0].content material.components[0].inline_data.information
wav_bytes = base64.b64decode(audio_data)
with open(“podcast.wav”, “wb”) as f:
f.write(wav_bytes)
print(“Podcast saved: podcast.wav”)

2. Execute it by executing the instructions proven under:

python podcast_gen.py

3. Open podcast.wav file and take heed to the 2 distinct voices representing the 2 personalities (the audio recordings may have been created with out using a recording studio).

Output:

Enhance it additional: To broaden upon this, level an online scrape software at any article you discover in a information supply or Reddit thread, create a 10-line abstract that converts that article right into a two-host debate-style script, and ship this to your podcast_gen.py. Now you should have an automatic “AI Day by day Information Podcast” that can run day by day out of your crontab.

App 3: Direct a Film Trailer Voice-Over utilizing Google AI Studio

The Banana Break up & Liberty Bell are collaborating to current you with a shocking film trailer voice-over. You may be doing every thing by way of the Google AI Studio browser console; due to this fact, there isn’t a want for coding or further setup. You’ll really feel utterly inventive on this mission, as you develop into the inventive director for this mission.

There are three components to this, and they’re as follows:

Prepared the Mannequin

1. Go to aistudio.google.com. As soon as there, log in along with your Google account. You’ll not want a bank card for the free-tier use of the service.

2. Select the Mannequin. As soon as logged in, choose the Gemini-3 TTS Preview. Will probably be titled on the right-hand sidebar beneath “Run Settings.”

Set the Scene

3. Use the textual content under to create a scene within the offered textbox on the prime of the Google AI Playground, earlier than you choose the masculine or female voice(s):

A darkish film theatre. The display sparkles. The viewers is holding their breath.

This can give the mannequin a context through which to take care of character for all of the audio system all through the manufacturing.

4. Create your Pattern Context. On this space kind: The narrator has simply accomplished a protracted silence. The bodily stress is at an unbelievable stage.

This tells the mannequin what kind of emotional state existed previous to the primary line of dialogue getting used.

Full Speaker Profiles

5. Full Speaker 1 – Zeph’s (Narrator) dialogue. Within the panel, you will note that Zephyr is designated as Speaker 1, with the descriptors of “Shiny, Greater pitch.” This means that he’s to be an pressing and fascinating narrator, good for an epic storyteller. Within the Speaker 1 dialogue block, kind the next:

[slow, deep, dramatic] In a world the place silence is taken into account “the regulation”,

[pause, building anxiety] one voice dares to talk.

[suddenly urgent, with intensity] They hunted her throughout the globe, and destroyed every thing they discovered.

[drops the intensity] Disappeared by any means obligatory.

Full Speaker 2 – Puck’s (Villain) dialogue. You will note that Puck has beforehand been designated as “Upbeat, Center pitch”; nevertheless, you’ll be able to overwrite that power with a temper tag. Within the Speaker 2 dialogue block, kind the next:

[cold, slow, with a menacing air] It is best to have by no means spoken.

[softly laughing, threat] There isn’t any one else coming that will help you.

Click on on “+ Add Speech Block” so as to add one other narrative closing for Speaker Zephyr’s narrative phase on the finish of this phase, and sort:

[booming, heroic voice] ECHOES. Coming quickly. Solely in theatres.

Output:

Benchmarks: How Does It Truly Stack Up?

At this level, we will see a completely totally different facet to the story. Whereas Google doesn’t say they’re higher than everybody else, they did submit their Gemini 3.1 Flash TTS (Textual content to Speech) to probably the most thorough unbiased benchmark TTS ever created.

The Synthetic Evaluation TTS Area runs 1000’s of nameless blind human choice exams on artificial speech. In these exams, individuals pay attention to 2 TTS voices and choose the one they imagine sounds probably the most pure, with out realizing which mannequin produced which voice. There isn’t any cherry-picking of samples or scores made by the corporate itself. That is the last word demonstration of how many individuals will desire utilizing every voice within the market. Listed below are a few of the outcomes of the Gemini 3.1 Flash TTS robotic:

1,211 Elo Rating at launch – the very best Elo rating for all publicly accessible TTS engines

“Most Engaging Change” placement – the one TTS within the historical past of TTS with each excessive naturalness and low value per character

70+ languages examined – all maintained natural-sounding fashion, pacing, and accent management

Produced three or extra totally different audio system in a single coherent output — not produced from concatenated clips

watermarked with SynthID within the output of every voice; no different mannequin on the leaderboard watermarks with SynthID.

Gemini 3.1 Flash TTS Comparability with Opponents

Most high-quality TTS engines usually are not reasonably priced. Most low-cost TTSes sound like TTSes that value an excessive amount of. Gemini 3.1 Flash TTS is the primary TTS to confidently place itself between these fashions. Right here’s the way it stacks up towards the main AI TTS fashions throughout standards that matter:

Conclusion

AI voice know-how has been round for a very long time, and it has been “ok” for a lot of makes use of. Nonetheless, AI voices weren’t “ok” for utilization in contexts that require a human voice to painting emotion, or to supply the person any type of inventive management.

Gemini 3.1 Flash TTS adjustments all of that. The wealthy set of options makes it the very first AI-based speech mannequin that may really compete with a recorded human voice, particularly to be used in inventive purposes.

The three tasks above are simply your entry level. Suppose interactive fiction with branching voiced narratives, multilingual customer support brokers with regional accents, and even AI tutors that sound like they care. With Gemini 3.1 Flash TTS, the sky is the restrict.