pocketsphinx VS webtransport

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've only tested Python to create a Native Messaging host https://github.com/guest271314/native-messaging-python and experiment with the deprecated QuicTransport https://github.com/guest271314/quictransport/blob/main/audioworklet-webassembly-memory-grow/quicTransportAudioWorkletMemoryGrow.js and WebTransport https://github.com/guest271314/webtransport.

One way to do that is utilizing Native Messaging on Chromium or Firefox https://github.com/guest271314/native-messaging-espeak-ng, and https://github.com/guest271314/webtransport/blob/main/webTransportEspeakNg.js for some WebTransport experiments. Technically we don't need a local server. We can stream and parse the WAV directly and pipe to AudioWorklet or a MediaStreamTrackGenerator https://github.com/guest271314/AudioWorkletStream. The same is true for speech recognition, where audio is piped to the local application and text or JSON piped back. Note also espeak-ng has been compiled to WebAssembly. I created native-messaging-espeak-ng for the ability to pass SSML directly to espeak-ng.

Yes, I am currently using https://github.com/guest271314/webtransport/blob/main/quic_transport_server_tts.py#L138.

You can use WebTransport in the browser (Chromium; Chrome) to run arbitrary Python (or other language the OS supports), e.g., see https://github.com/guest271314/webtransport.