I worked with this a bit not that long ago. For cloud services, quality of Google and Azure "neural" voices are tough to beat. Interestingly I experienced signi

I worked with this a bit not that long ago. For cloud services, quality of Google and Azure "neural" voices are tough to beat. Interestingly I experienced significant latency for all of the Azure services regardless of region, configuration, etc. Never dug deep enough to figure out what was going on there. Also of note, Azure will let you run their implementation on a local container with the usual "contact us" stuff. Not sure of the terms and pricing on that. For local, Mozilla TTS was best from a quality standpoint but the GPU inference support was a bit dicey and (possibly) not really supported at all. For more complex and bespoke applications the Nvidia (I know, I know) NeMO toolkit [0] is very powerful but requires more effort than most to get up and running. However, it provides the ability to do very interesting things with additional training and all things speech. In the Nvidia world there's also their Riva [1] (formerly Jarvis) solution that works with Triton [2] to build out an architecture for extremely performant and high-scale speech applications with things like model management, revision control, deployment, etc. [0] https://github.com/NVIDIA/NeMo https://github.com/NVIDIA/NeMo [1] https://developer.nvidia.com/riva https://developer.nvidia.com/riva [2] https://developer.nvidia.com/nvidia-triton-inference-server https://developer.nvidia.com/nvidia-triton-inference-server