The people calling it "OK" probably tried it for themselves. Whatever model is being demoed in that video is not the same as the 25MB model they released.
It doesn't sound so good. Excellent technical achievement and it may just improve more and more! But for now I can't use it for consumer facing applications.
Speech speed is always a tunable parameter and not something intrinsic to the model.
The comparison to make is expressiveness and correct intonation for long sentences vs something like espeak. It actually sounds amazing for the size. The closest thing is probably KokoroTTS at 82M params and ~300MB.
The only real questions are which Chinese gacha game they ripped data from and whether they used Claude Code or Gemini CLI for Python code. I bet one can get a formant match from output this much overfit to whatever data. This isn't going to stay up for long.
Impressive technical achievement, but in terms of whether I'd use it: oof, that male voice is like one of these fake-excited newsreaders. Like they're always at the edge of their breath. The female one is better but still someone reading out an advertisement for a product they were told they must act extra excited for. I assume this is what the majority of training data was like and not an intentional setting for the demo. Unsure whether I could get used to that
I use TTS on my phone regularly and recently also tried this new project on F-Droid called SherpaTTS, which grabs some models from Huggingface. They're super heavy (the phone suspends other apps to disk while this runs) and sound good, but in the first news article there were already one or two mispronunciations because it's guessing how to say uncommon or new words and it's not based on logical rules anymore to turn text into speech
Google and Samsung have each a TTS engine pre-installed on my device and those sound and work fine. A tad monotonous but it seems to always pronounce things the same way so you can always work out what the text said
Espeak (or -ng) is the absolute worst, but after 30 seconds of listening closely you get used to it and can understand everything fine. I don't know if it's the best open source option (probably there are others that I should be trying) but it's at least the most reliable where you'll always get what is happening and you can install it on any device without licensing issues
anyone else wants to try sherpaOnnx you can try this.. https://github.com/willwade/tts-wrapper we recently added in the kokoro models which should sound a lot better. There are a LOT of models to choose from. I have a feeling the Droid app isnt handling cold starts very well.
And a quick video with all of the different voices:
https://www.youtube.com/watch?v=60Dy3zKBGQg
Thanks. I really would not want to listen to any of these regularly.
Cool, thanks... aside: the last male voice sounds high/drunk.
thank you!
The reddit video is awesome. I don't understand how people are calling it an OK model. Under 25MB and cpu only for this quality is amazing.
The people calling it "OK" probably tried it for themselves. Whatever model is being demoed in that video is not the same as the 25MB model they released.
Nope, looks like the default voice is the worst and it's not in the demo. A Reddit user generated these as well https://limewire.com/d/28CRw#UPuRLynIi7
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It did say this was a preview release, so I'll reserve judgement until that's out the door.
Local quality is very bad
https://vocaroo.com/1njz1UwwVHCF
It doesn't sound so good. Excellent technical achievement and it may just improve more and more! But for now I can't use it for consumer facing applications.
We are still training the model. We expect the quality to go up in the next release. This is just a preview release :)
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Sounds very clear. For a non native english speaker like me, it's easy to understand.
Sounds slow and like something from an anine
Speech speed is always a tunable parameter and not something intrinsic to the model.
The comparison to make is expressiveness and correct intonation for long sentences vs something like espeak. It actually sounds amazing for the size. The closest thing is probably KokoroTTS at 82M params and ~300MB.
I think he meant overacting typical for English dubs.
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The only real questions are which Chinese gacha game they ripped data from and whether they used Claude Code or Gemini CLI for Python code. I bet one can get a formant match from output this much overfit to whatever data. This isn't going to stay up for long.
was it cross trained on futurama voices?
That would be a feature!
Sounds like Mort from Family Guy.
Lol
It was not
Impressive technical achievement, but in terms of whether I'd use it: oof, that male voice is like one of these fake-excited newsreaders. Like they're always at the edge of their breath. The female one is better but still someone reading out an advertisement for a product they were told they must act extra excited for. I assume this is what the majority of training data was like and not an intentional setting for the demo. Unsure whether I could get used to that
I use TTS on my phone regularly and recently also tried this new project on F-Droid called SherpaTTS, which grabs some models from Huggingface. They're super heavy (the phone suspends other apps to disk while this runs) and sound good, but in the first news article there were already one or two mispronunciations because it's guessing how to say uncommon or new words and it's not based on logical rules anymore to turn text into speech
Google and Samsung have each a TTS engine pre-installed on my device and those sound and work fine. A tad monotonous but it seems to always pronounce things the same way so you can always work out what the text said
Espeak (or -ng) is the absolute worst, but after 30 seconds of listening closely you get used to it and can understand everything fine. I don't know if it's the best open source option (probably there are others that I should be trying) but it's at least the most reliable where you'll always get what is happening and you can install it on any device without licensing issues
anyone else wants to try sherpaOnnx you can try this.. https://github.com/willwade/tts-wrapper we recently added in the kokoro models which should sound a lot better. There are a LOT of models to choose from. I have a feeling the Droid app isnt handling cold starts very well.
If anyone wants to test ready to install android apks: https://k2-fsa.github.io/sherpa/onnx/tts/apk.html
Thanks a lot for the detailed feedback. We are working on some models which do not use a phonemizer
RHvoice is pretty good, imho.