Pet peeve on Google's AI rollouts: there's no alignment across the three platforms they have, consumer, prosumer, cloud. Scroll to the end of every release, including this one, and you'll see different availabilities. The fun part is the models don't even have the same capabilities across platforms! Omni Flash, last I tried and read the docs, is video and text out on consumer and prosumer but video out only on GCP. So if your org disables consumer and prosumer, like mine, it's a coin flip whether you can use the fancy new models or what they can do.
> Pet peeve on Google's AI rollouts: there's no alignment across the three platforms they have...
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".
I hear much of what happens there is from PMs who want promotions, which makes me wonder if a goal (like interorg alignment) could be met by freezing their promotions until they Google Meet together & hash it out.
I’m reducing into silliness I’m sure, I don’t have any breadth or depth of knowledge here.
Edit: wonder why Apple is ostensibly different. MS seems similar, and don’t know enough about AWS—maybe I’ve seen complaints about them being disjointed, but not as much as Google & Microsoft.
> Voice replication: Recreate consistent vocal profiles from just a 30-second audio sample of your voice or a voice you have the rights to use, backed by built-in consent verification, SynthID watermarking, and C2PA credentials to protect both developers and their vocal talent.
I guess voice cloning is widely enough available now from other providers that Google are no longer hesitant to ship it.
Yesterday night I was doing a project with QwenTTS 1.7B.
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 one of my interests is reducing the payload size for video games
the vast majority of the image sizes have been audio recordings, and its been that way in different qualities for the last two decades. this is still the case as more varied and comprehensive audio is pursued by studios at unfathomable expense and still failing to cross a bar of realism
good voice models are just a few gigabytes in comparison and can supplant all of that, and be run locally at this point. Future ubiquitous hardware configurations in consumer devices will make inference dedicated and computationally cheaper and faster
although AAA studios are hamstrung and will be deeply unpopular if they stopped booking voice actors
everyone else who would have never had the capital for voice actors will just use this and have richer experiences until they themselves are AAA studios from the market buying their rich experiences
this will vastly supplant the assumed and uninspired “tricking humans” use case from that video. once it crosses a threshold of ease, the applications will expand
They probably do something similar to GPT-Live where they expect a given voice profile to send them a sample saying 'This is the owner of this voice and I consent for synthetic samples to be made of it'
and/or local voice cloning is good enough as is so Google doesn't grant a uniquely liable ability?
>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.
This has been possible for quite a long time (probably 1-2 years). There are multiple open models that can do this quite well. Recent example from my YT feed:
usually people bring up anyone who is losing physical control of their voice faculties, so they can have a synthetic voice that matches their natural voice
The iPhone has a built in voice cloner hidden in the accessibility settings for exactly this use-case: creating a backup of your voice in case you need it in the future.
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.
I mean yeah? If google offers a cloud nmap tool, should everyone get in a tizzy about how google is "evil", even though it saves baddies maybe 5 minutes of work?
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.
I've been working on a similar project all year and as a tip, you should try Fish Audio or Higgs as a replacement for Qwen3. Both yield much better prosody and are much easier to listen to for long runs.
I wasn't able to find a version of these that can create voice samples based on voice designs. Do you mean to use Qwen3 TTS Voice Design to create samples followed by Higgs or Fish Audio to clone the sample voices and narrate the novel?
MOSS-TTS 2.0 will apparently have voice design, as well, on par with ElevenLabs quality.
For the voice design, these don’t support it, but for the final render, they’re much better. So your pipeline could for example generate voices with one tool and render with another.
It's cool technology and I read a lot of audiobooks, even hundreds of hours of TTS. I feel like my brain can fill in the character voices from the text - on the page it's not like they're different fonts.
I understand audiobook narrators often do it, and that's fun. But it's not so critical in my opinion
> annotate your text with extra 'stage directions'
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.
I direct my own extended daydream Star Trek fanfic (okay, I'm on season 2 episode 17) and recently I looked to see if I could have each scene file be read aloud a la an audiobook or radio drama.
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.
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!
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.
Doesn't actually read the page, though. Or not what you see in the browser. For example right now, when I navigate to "reply" it doesn't read the comment I'm replying to - it's reading the login banner you get visiting a reply link without being logged in.
I vibed a wikipodcast app that has a wikipedia dump, gemma llm for search and summarization and a tts model for audio gen so I could just ask about topics while on the go, and the app would just go off and tell me stuff out of the Wikipedia database.
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.
It's giving me an error when I try to generate a voice with Voice Design in AI Studio. It also says voice replication isn't available in my region.
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.
It depends on what you are after (quality, legibility, performance, etc.).
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.
I've got the best results with BreezeTTS, Higgs Audio v3, and Fish Audio S2 Pro. audio.cpp (https://github.com/0xShug0/audio.cpp) is an easy way to run a lot of different models.
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.
I gave 3.8 a whirl today, replacing Eleven v3 TTS in an internal application that uses TTS to provide a listening function. The Google model produces extremely expressive output. To my ears, it’s on par with Eleven v3, which was already amazing.
Nice work. It’s awesome to have these capabilities so close at hand and so trivially easy to integrate with.
I vibe coded a playground UI for trying this out. The conversation mode is neat, and it's very expensive - most of my experiments have cost less than a cent.
Nice but in general I wouldn't put my API key into some third party website, no matter if it claims to not store it. It's not something personal, you are a bit of a celeb here so I wouldn't think you'd save the keys, it's just good general data hygiene. Especially not if a leaked API key can rack up thousands of dollars in fees quickly.
"Super tinny monotone robotic voice" does not sound neither tinny nor monotone. Compared to what TTS from 90s sounded like. Or even how actors impersonated robots in movies. Has the model been eating too much hype DJs?
None of these examples are really what the prompt asked for. It's just like image models, once you get over how unbelievable it is that a computer produced this you realize the result isn't actually what you want.
Seems like voice actors are safe for now. This is technologically incredible, but the results are really not very good, and usually not particularly close to the prompt. In basically all of these examples some core part of the prompt is completely ignored.
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.
Technologically incredible as in "I cannot believe it's possible for a computer to do this" and not very good as in "these examples are not what was prompted and I can't think of a use case where these would be acceptable".
Imagine someone showing you that they've trained their dog to hold a paintbrush and paint. There would be no contradiction between "this is incredible" and "these paintings suck".
Interesting to see that they are publishing a new tts model. I remember that they refused to release one of them a few years ago because they were too afraid of abusing it. Now they just release it without any much thought lol
Sorry if this is in that article, but I am on my phone and can't see it. How much would this cost to batch generate an audiobook? Right now I just listen to things in the 11 labs app which is free, but I would rather just generate audio files.
That is the biggest difference here for me. I have not looked at every solution, but many. They are either much more expensive or garbage quality. For example my next target audiobook is a monster 250k words, 1.5m characters, so about $15 here or $75 using elevenlabs (0.05 per 1k characters). For me that is the difference between I will or I won't use it.
In their demo for "Monologue" (2nd video over, after the medeival video game example), it is clearly ignoring the vocal cues like `<chuckles>` and `<laughing>`...
Honestly I think their approach is the long term most useful one. Being SOTA is probably very costly and difficult. Optimising all the smaller stuff that's real world useful for people seems like it would have better long term use.
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
I can see where you are coming from. Vendor lock-in.
Basically spread many AI's everywhere, get people develop/user their ecosystem, and lock them in eventually.
But I find their models' intelligence lacking still.
I don't ever use their built-in gemini features (i have paid gmail) because they don't work well.
e.g. I ask gemini to format my Google docs per Google's material design spec with spacing, etc.
It does a real bad job. Many times it does it line by line, and when I finaly get it do it for the whole doc, it does it sloppy, and extremely slow (takes 5 minutes for 10 page doc)
Still, all voices sound like they are missing something only real human speech can sound like. But many people will not notice the difference between AI and normal voices.
Probably $$$ and limit to internal compute. Rumour is they even internal google employees have trouble getting compute for AI stuff. Guessing they're pretty slammed infrastructure wise with adding AI answers to default Google searches
Yes, I find nearly every "SOTA" voice model I try intolerable to listen to because of the fake exaggerated expression/emotion. It's actively distracting because it pulls focus to emphasize randomly. ChatGPT Voice models are so insufferable to put up with for a conversation longer than 45 seconds.
All I want is a clear, technically flawless, even/restrained "computer voice" for pretty much every use case (except audiobooks). But that doesn't make for splashy demos/score well for RLHF raters.
Yes, I wish there was more focus on correct pronunciation over emotion. You need a mechanism to control/guide the voice which gets under balance right between not having to specify everything and still letting you fix certain cases (where you know a certain sense of a word is meant)
The first <sigh> does sound a lot like a moan. OP linked to the timestamp so I missed it when it first played. I was also confused but on second playback I heard the first <sigh> and also thought wtf.
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".
I’m reducing into silliness I’m sure, I don’t have any breadth or depth of knowledge here.
Edit: wonder why Apple is ostensibly different. MS seems similar, and don’t know enough about AWS—maybe I’ve seen complaints about them being disjointed, but not as much as Google & Microsoft.
Googly way to put it! Nice. Might steal that :)
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
https://youtu.be/M-IVVJkZnuo?t=236
so one of my interests is reducing the payload size for video games
the vast majority of the image sizes have been audio recordings, and its been that way in different qualities for the last two decades. this is still the case as more varied and comprehensive audio is pursued by studios at unfathomable expense and still failing to cross a bar of realism
good voice models are just a few gigabytes in comparison and can supplant all of that, and be run locally at this point. Future ubiquitous hardware configurations in consumer devices will make inference dedicated and computationally cheaper and faster
although AAA studios are hamstrung and will be deeply unpopular if they stopped booking voice actors
everyone else who would have never had the capital for voice actors will just use this and have richer experiences until they themselves are AAA studios from the market buying their rich experiences
this will vastly supplant the assumed and uninspired “tricking humans” use case from that video. once it crosses a threshold of ease, the applications will expand
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://m.youtube.com/watch?v=WENMgQE9tws
https://en.wikipedia.org/wiki/Sarah_Langs
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 wasn't able to find a version of these that can create voice samples based on voice designs. Do you mean to use Qwen3 TTS Voice Design to create samples followed by Higgs or Fish Audio to clone the sample voices and narrate the novel?
MOSS-TTS 2.0 will apparently have voice design, as well, on par with ElevenLabs quality.
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...
https://m.youtube.com/watch?v=jDudeaWppSE
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.
Please let me know if you have any questions or feedback.
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.
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.
Having a voice under 1Mo is crazy, even if it sounds robotic.
https://tts.ampixa.com/sanoTTS/
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.
Nice work. It’s awesome to have these capabilities so close at hand and so trivially easy to integrate with.
https://tools.simonwillison.net/gemini-tts-playground#compos...
https://aistudio.google.com/generate-speech?model=gemini-3.8...
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?
Um, what?
They sounded exactly like that person... but it's like they're angry at me.
Great toys but not production ready.
Imagine someone showing you that they've trained their dog to hold a paintbrush and paint. There would be no contradiction between "this is incredible" and "these paintings suck".
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
Official pricing can be seen here: https://ai.google.dev/gemini-api/docs/pricing#gemini-3.8-fla...
$0.50 per hour pricing could last a long time with back and forth conversation use.
They are creating gemini SOTA (not really any more), flash versions, text-to-speech, video (omni), etc.
I can see they want to create an ecosystem, but I see no focus in any one area.
At best, good, but not great.
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
Basically spread many AI's everywhere, get people develop/user their ecosystem, and lock them in eventually.
But I find their models' intelligence lacking still.
I don't ever use their built-in gemini features (i have paid gmail) because they don't work well.
e.g. I ask gemini to format my Google docs per Google's material design spec with spacing, etc. It does a real bad job. Many times it does it line by line, and when I finaly get it do it for the whole doc, it does it sloppy, and extremely slow (takes 5 minutes for 10 page doc)
And yeah integration with Google Workspace is still surprisingly not as good as you would expect.
The original is the best: https://youtu.be/qxWwEPeUuAg
They all sound like Americans putting in their best fake British accent.
All I want is a clear, technically flawless, even/restrained "computer voice" for pretty much every use case (except audiobooks). But that doesn't make for splashy demos/score well for RLHF raters.
Also HN: Fuck those voice actors and their careers.
Onomatopoeia? Sure it is there, and some fillers (or whatever you call those little sounds). But moans?
I would not want that in my product.