Gemini 3.8 text-to-speech (blog.google)

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.

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".

and/or local voice cloning is good enough as is so Google doesn't grant a uniquely liable ability?

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.

https://m.youtube.com/watch?v=WENMgQE9tws

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.

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?

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...

https://m.youtube.com/watch?v=jDudeaWppSE

https://support.google.com/chrome/answer/14768725?hl=en

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.

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.

https://aistudio.google.com/generate-speech?model=gemini-3.8...

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.

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.

On top of that I would imagine the research side of Google might disk over things from one modality being useful to another - something like an audio optimising or memory optimising for text to speech could maybe also be useful for translation or world models. Etc etc

Um, what?

I listened to some of the voices. The male voices are believable while all the female voices sound the same and artificial. For some reason, it also reminds me of the voices in Toy Story movies.

Bias in the training data?

Price per hour:

- 3.8 Flash TTS, standard: $0.81

- 3.8 Flash TTS, batch: $0.41

- 3.8 Flash‑Lite TTS, standard: $0.54

- 3.8 Flash‑Lite TTS, batch: $0.27