The real value I see is being able to clone a voice and change timbre and characteristics of the voice to be able to quickly generate voice overs, narrations, voice acting, etc. It's superb!
Well, if you look at the prompts, they are basically told to sound like that.
And if you ask me, I think these models were trained on tween fiction podcasts. (My kids listen to a lot of these and dramatic over-acting seems to be the industry standard.)
Also, their middle-aged adult with an "American English" accent sounds like any American I've ever met. More like a bad Sean Connery impersonator.
I suspect they might be using voice lines from Chinese gacha games in addition to what clearly sound like VTubers, YouTubers, and Chinese TV documentary narrations. Those games all come with clean monaural CN/JP/EN files consistent in contents across language for all regions, for, an obvious[1] reason.
it isn't often that tehcnology gives me chills, but this did it. I've used "AI" TTS tools since 2018 or so, and i thought the stuff from two years ago was about the best we were going to get. I don't know the size of these, i scrolled to the samples. I am going to get the models set up somewhere and test them out.
Now, maybe the results were cherrypicked. i know everyone else who has released one of these cherrypicks which to publish. However, this is the first time i've considered it plausible to use AI TTS to remaster old radioplays and the like, where a section of audio is unintelligible but can be deduced from context, like a tape glitch where someone says "HEY [...]LAR!" and it's an episode of Yours Truly, Johnny Dollar...
I have dozens of hours of audio of like Bob Bailey and people of that era.
If you want to try out the voice cloning yourself you can do that an this Hugging Face demo: https://huggingface.co/spaces/Qwen/Qwen3-TTS - switch to the "Voice Clone" tab, paste in some example text and use the microphone option to record yourself reading that text - then paste in other text and have it generate a version of that read using your voice.
Has anyone successfully run this on a Mac? The installation instructions appear to assume an NVIDIA GPU (CUDA, FlashAttention), and I’m not sure whether it works with PyTorch’s Metal/MPS backend.
I see a lot of references to `device_map="cuda:0"` but no cuda in the github repo, is the complete stack flash attention plus this python plus the weights file, or does one need vLLM running as well?
Haha something that I want to try out. I have started using voice input more and more instead of typing and now I am on my second app and second TTS model, namely Handy and Parakeet V3.
Parakeet is pretty good, but there are times it struggles. Would be interesting to see how Qwen compares once Handy has it in.
Interesting model, I've managed to get the 0.6B param model running on my old 1080 and I can generated 200 character chunks safely without going OOM, so I thought that making an audiobook of the Tao Te Ching would be a good test. Unfortunately each snippet varies drastically in quality: sometimes the speaker is clear and coherent, but other times it bursts out laughing or moaning. In a way it feels a bit like magical roulette, never being quite certain of what you're going to get. It does have a bit of charm, when you chain the various snippets together you really don't know what direction it's gonna go.
Using speaker Ryan seems to be the most consistent, I tried speaker Eric and it sounded like someone putting on a fake exaggerated Chinese accent to mock speakers.
If it wasn't for the unpredictable level of emotions from each chunk, I'd say this is easily the highest quality TTS model I've tried.
Can anyone please provide directions/links to tools that can be run locally, and that take an audio recording of a voice as an input, and produce an output with the same voice saying the same thing with the same intonations, but with a fixed/changed accent?
This is needed for processing an indie game's voice recordings, where the voice actors weren't native speakers and had some accent.
Amusingly one of their examples (the final Age Control example) is prompted to have American English as an accent, but sounds like an Australian trying to sounds American to my ear haha
Is there any way to take a cloned voice model and plug into Android TTS and/or Windows?
I have a friend with a paralysed larynx who is often using his phone or a small laptop to type in order to communicate. I know he would love it if it was possible to take old recordings of him speaking and use that to give him back "his" voice, at least in some small measure.
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[ 2.9 ms ] story [ 49.4 ms ] thread100% I was thinking the same thing.
And if you ask me, I think these models were trained on tween fiction podcasts. (My kids listen to a lot of these and dramatic over-acting seems to be the industry standard.)
Also, their middle-aged adult with an "American English" accent sounds like any American I've ever met. More like a bad Sean Connery impersonator.
1: https://old.reddit.com/r/ZenlessZoneZero/comments/1gqmtl1/th...
Although I like the model, I don't like the leadership of that company and how close it is, how divisive they're in terms of politics.
Now, maybe the results were cherrypicked. i know everyone else who has released one of these cherrypicks which to publish. However, this is the first time i've considered it plausible to use AI TTS to remaster old radioplays and the like, where a section of audio is unintelligible but can be deduced from context, like a tape glitch where someone says "HEY [...]LAR!" and it's an episode of Yours Truly, Johnny Dollar...
I have dozens of hours of audio of like Bob Bailey and people of that era.
I shared a recording of audio I generated with that here: https://simonwillison.net/2026/Jan/22/qwen3-tts/
Parakeet is pretty good, but there are times it struggles. Would be interesting to see how Qwen compares once Handy has it in.
Using speaker Ryan seems to be the most consistent, I tried speaker Eric and it sounded like someone putting on a fake exaggerated Chinese accent to mock speakers.
If it wasn't for the unpredictable level of emotions from each chunk, I'd say this is easily the highest quality TTS model I've tried.
This is needed for processing an indie game's voice recordings, where the voice actors weren't native speakers and had some accent.
Here's the script I'm using: https://github.com/simonw/tools/blob/main/python/q3_tts.py
You can try it with uv (downloads a 4.5GB model on first run) like this:
I have a friend with a paralysed larynx who is often using his phone or a small laptop to type in order to communicate. I know he would love it if it was possible to take old recordings of him speaking and use that to give him back "his" voice, at least in some small measure.