pocketsphinx VS espeak-ng

There are espeak-ng https://github.com/espeak-ng/espeak-ng and pocketsphinx https://github.com/cmusphinx/pocketsphinx which can be used locally without making external requests.

And so I installed PocketSphinx, "one of Carnegie Mellon University's open source large vocabulary, speaker-independent continuous speech recognition engines."

- https://github.com/cmusphinx/pocketsphinx

This avoids having to stream audio 24x7 to a cloud model which would be super expensive. This being said, I'm pretty sure what the Alexa does, for example, is send any positive wake word to a cloud model (that is bigger and more accurate) to verify the prediction of the local wake word detection model AFAIK.

PocketSphinx is generally regarded among voice assistant communities as a less reliable, but straight OOTB, alternative to a robust listener. It's a good solution when you want multiple hotwords (or just aren't in a position to train even one word.)

I'm skeptical about a senior JavaScript developer claiming to be bored. Nonetheless, let's see. How would you go about modifying [this](ng/blob/master/emscripten/espeakng_glue.idl) IDL file, this C++ glue code, and the relevant Make file to compile eSpeak NG to JavaScript with Emscripten with SSML support enabled?

eSpeak NG supports running on Linux, BSD, Mac, Android, Windows, has been compiled to WASM with Emscripten. See also espeak and meSpeak.js.

I may have a solution, BUT I'm at an airport right now, so... Perhaps tonight I can give you some ideas. There is a program I used to make a few presets for myself. https://github.com/espeak-ng/espeak-ng/blob/master/docs/languages.md

For this one, I used espeak (https://github.com/espeak-ng/espeak-ng) as a text processor. It is almost 17 years old software and is pretty lacking, unfortunately. On the other hand, it's super fast and supports tens of languages. Long story short, punctuation introduces phrase break with a pause of fixed length, and capitalization is ignored.

I didnt not release trainy parts to build voices. I am considering, but there is so many packages already (coqui, espnet, piper, nemo, fairseq to name a few) that i focused on usability for now. Support for new languages is a different question. Everyone wants to train fancy neural nets. But support for new language is about writing rules and having language expertise. I did it for English (https://github.com/balacoon/en_us_normalization/tree/c1019cf878aa6baf25d6fff719cf418cca5a3107/production/classify). Doing it for all the other languages would probably take me a lifetime. Other speech synthesis solutions use 17-years old espeak for this purpose (https://github.com/espeak-ng/espeak-ng/blob/master/docs/languages.md). I introduced the fallback to it in Balacoon too. But generally, it is outdated technology and I believe we should do better.

espeak-ng works by first converting text to IPA and then pronouncing that. But im not sure im aware of a way to input arbitrary IPA, and also the quality is probably too low for you.

There are espeak-ng https://github.com/espeak-ng/espeak-ng and pocketsphinx https://github.com/cmusphinx/pocketsphinx which can be used locally without making external requests.

There are automatic tools to convert a written form of a language to IPA, I'm personally aware of espeak-ng, which supports* a lot of languages.

I've had good luck with https://github.com/espeak-ng/espeak-ng (for very specific purposes, and I was willing to wrangle IPA)