This is really cool work! I'm curious like what do you see as the biggest lever for speeding up TTS models or from a technical perspective that this was a promising direction in the first place to push on. If I were to guess, some distillation but I'm certain there are probably TTS model aware architectural changes that just make inference wayyyy faster?
By next month the competition for TTS will be even more!
Voice models are not winner take all market unlike LLM APIs
Coming here as Developer Relations at AssemblyAI
Cool, I’ve released something to the same beat of the dr this weekend as well
https://github.com/loudreader/loudkit
I think real time natural tts should be possible everywhere soon
Rooting for you on this one.
You definitely need independent evals by Datapoint AI or someone who can verify your claims about TTS quality
For some reason it switched voices half way through a 33 second clip.
For OP the clip name is nari-nina-01a0a12f-980a-765e-8029-fa56bd23210d.wav
If you're going to announce a TTS model, service, or whatever, you really need demos.
This is really cool work! I'm curious like what do you see as the biggest lever for speeding up TTS models or from a technical perspective that this was a promising direction in the first place to push on. If I were to guess, some distillation but I'm certain there are probably TTS model aware architectural changes that just make inference wayyyy faster?
> and Qwen3-ASR
Is the ASR inference engine open source as well?