just remember: despite they would have you believe they are are a united front... they are better thought of as a "loose federation of warring tribes".
My personal account, 3.6 Flash Lite and 3.5 Thinking.
Meanwhile, I can go hog wild and drain my bank account on GCP. I don’t though, because my family has to eat.
I guess voice cloning is widely enough available now from other providers that Google are no longer hesitant to ship it.
After some debugging, making a clean dataset with clean recordings, and experimenting with a good fine tune recipe (much props to the new GPT models yesterday being cheaper).
I was able to make a robo-me that sounds absurdly good, family was shocked, all in a matter of a few hours.
So yeah the cat is out of the bag for sure.
It took like 1min - capture something from a youtube or video and put in your own text. It worked also really good for a german test.
Made a voice message for my wife from one of our favorite actors, telling here how nice it would be to make some breakfast :D
and/or local voice cloning is good enough as is so Google doesn't grant a uniquely liable ability?
Probably the latter. Cat's already out of the bag to the extent that you can synthesize with a specific voice in one go and it sounds decent. Even if you need commercial models for better intonation or whatever, you can probably get the commercial models to first generate with a generic voice, then use a local model to transfer that to voice you're cloning. That'll probably get rid of any C2PA watermarks too.
https://abc.xyz/investor/board-and-governance/google-code-of...
ctrl/cmd+f "evil"
I don't know why this argument is brought up all the time anyway, it literally means nothing. They can name themselves "Don't Be Evil Inc" and continue to do evil stuff cause evil isn't an objective measure. If squeezing juice out of puppies made money, any business can just say it's "not evil."
And if you think they're evil why would you trust them to follow their own guideline of not doing evil? An evil corp would be more likely to just hide behind that phrase, not quietly remove it as some subtle hint that they want to be openly and proudly evil all of a sudden.
https://www.youtube.com/watch?v=WAeHgE94rVo
No cloud, no tokens to pay. Reads a book using a full cast of characters. Quotation attribution detection (for my novel) is at 97.2% accuracy (485/499 quotes identified and assigned correctly). The autofill of character voice descriptions uses the prose to determine how the character sounds.
Employs Gemma 4[1] for the prose analysis (voice fills, quotation detection) and Qwen3 TTS Voice Design[2] for creating voice samples. Runs on an 8GB NVIDIA T1000 GPU card, 96 GB RAM, and a AMD Ryzen 5 7600.
[1]: https://deepmind.google/models/gemma/gemma-4/
[2]: https://huggingface.co/spaces/Qwen/Qwen3-TTS-Voice-Design
I understand audiobook narrators often do it, and that's fun. But it's not so critical in my opinion
Is it possible to annotate your text with extra 'stage directions' that influence how the book is read out?
Good idea, not something I've considered yet. Wouldn't take much to add it since there's already a feature for selecting a quotation and assigning it an intonation. Same infrastructure could be reused to select arbitrary text and assign stage directions.
The title of the video is 'KeenLore - Emotive Audiobook Creator Demo' and it appears to be a web UI and some local stack that reads text files.
Getting GPT-Live to have unique enough voices and to be expressive with how I imagine the voices going in my head is hard to direct, there's not enough control there.
So this Gemini 3.8 specific large voice library and ability to tightly control (if you are willing to write a script) is nice to find, and while I'm not sure which of the 5,286 Gemini products this is, nor how to onboard and get started feeding this my own text files, nor what training will happen to my data if I did somehow use it, I love that the state of the industry is such that Google can do this and release it publicly, because that means eventually an equivalent product can come from someone else and be used locally / confidently that the generated audio or inputs won't be retained and misused.
Also the Qwen3-TTS demo is cool, you can describe the voice you want: https://huggingface.co/spaces/Qwen/Qwen3-TTS
I came across both on this subreddit, it's very active: https://www.reddit.com/r/TextToSpeech/
I'm personally using this locally: https://github.com/mateogon/pdf-narrator (it's a Python frontend for Kokoro) on my M1 Macbook Air (from 2020, with 8GB RAM) and it's incredible. I make my own audiobooks now - for free!
My favorite voice is am_michael and here's a sample: https://voicerankings.com/voice/kokoro-82M/male/am_michael/s...
Is there a good browser extension that does this with a flexible TTS backend? I know Qwen, Kokoro, and VibeVoice all have decent quality..
I found all these on this subreddit: https://www.reddit.com/r/TextToSpeech/
I've also see comments like "Microsoft Edge's read-aloud feature is amazing for TTS" but I haven't tried it myself.
Personally I use Kokoro with a python front-end on my Macbook, I linked to it in this comment: https://news.ycombinator.com/item?id=49818923 it outputs MP3, so I just copy those to my phone and listen as audiobooks.
It was especially nice during a bike trip along the Rhine, I listened to a lot of the history of the industrial area and its cities.
How long is this stored? What could go wrong? :P
Also weird that there are no "neutral gender" voices in the English language. There's also limited "use cases," like the "Gaming" use case is empty?
And there's no pricing listed anywhere.
I don't know, I guess their roll out is a bit sloppy. It's a bit of a shame, though, since the voices which are available all sound like generic Gemini voices to me. Nothing stands out is being particularly interesting or impressive about this.
If you're after quality then Qwen3 TTS is a very good model esp. if you take some effort to craft a voice file. It is slow, so isn't practical for real-time voices (like assistants). It can also occasionally switch to a different voice to the one provided, so you may want to break up the text being processed.
I've not yet tried other recent/recentish models.
If you are after performance then two options from older models are:
1. flite with a HTS (Hidden Markov Model) voice like cmu_us_rms (male) or cmu_us_slt (female);
2. espeak/espeak-ng with an MBROLA (an Overlapped Add model) voice (mb-us1, mb-de5-en, etc.).
Alternatively, you could try using Qwen3 TTS or over voice changing model with the CMU Arctic (http://www.festvox.org/cmu_arctic/) voice data which includes audio for the rms and slt voices among others.
If you're feeling adventurous you could also try fine tuning one of the TTS models on that data to create a custom voice, though the data is likely to be in the training data for the voices, so using an audio sample may be sufficient depending on the TTS model.
Different models have different strengths. If you throw an entire ebook at a model you're going to get a different result than if you craft a perfect 10 second sentence with a model that supports voice direction and emotion tags, so you should try a bunch depending on your use case.
https://tools.simonwillison.net/gemini-tts-playground#compos...
https://aistudio.google.com/generate-speech?model=gemini-3.8...