vosk-api

first, good initiative! thanks for sharing. i think you gotta be more diligent and careful with the problem statement. checking the weather in Sofia, Bulgaria requires cloud, current information. it's not "random speech". ESP SR capability issues don't mean that you cannot process it locally. the comment was on "voice processing" i.e. sending speech to the cloud, not sending a call request to get the weather information. besides, local intent detection, beyond 400 commands, there are great local STT options, working better than most cloud STTs for "random speech" https://github.com/alphacep/vosk-api https://picovoice.ai/platform/cheetah/

I've been using the Azure Cognitive Services speech recognition and text-to-speech for my own locally run 'speech-to-speech' GPT assistant application. I found the Azure speech recognition to be fantastic, almost never making mistakes. The latency is also at a level that only the big cloud providers can reach. A locally run alternative I use is Vosk [0] but this is nowhere near as polished as Azure speech recognition and limits conversation to simple topics. (Running whisper.cpp locally is not an option for me, too heavy and slow on my machine for a proper conversation) The default Azure models available for text-to-speech are great too. There are around 500 models in a wide variety of languages. Using SSML [1] can also really improve the quality of interactions. A subset of these voices have certain capabilities (like responding with emo