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A high-end phone is quite capable of doing automatic speech recognition continuously, as well as NLP topic analysis. The last years voice activity detection has
by jononor 4y ago
A high-end phone is quite capable of doing automatic speech recognition continuously, as well as NLP topic analysis. The last years voice activity detection has moved down into the microphone itself, to enable ultra low power always-listening functionality. It then triggers further processing of the potentially-containing-speech audio.
Modern SoC have dedicated microcontroller/microprocessor cores that can do further audio analysis, without involving the main cores or the OS. Typically deciding if something is speech or not. Today this is usually doing Keyword Spotting (hey Alexa etc).
These are expected to get access to neural accelerators chips, which will further improve power efficiency and eventually having sufficient memory and computer to run speech recognition. So the technological barriers are falling one by one.
- dbish 4y agoI worked on Alexa (and Cortana before that). I’m aware of the current tech. The tech barriers for doing this at high accuracy cheaply are still very much there.
- jononor 4y agoWhich barriers do you considered to be the most problematic (and why)? I think that using todays CPU/GPU on a modern phone, one would be able to run a model capable of a Word Error Rate of under 10%. I mean, it would take up maybe 1GB of RAM. And battery life would be impacted, but still a quite usable phone? And that seems like it would give workable quality data for some topic / user modelling? I am assuming one would limit triggers to cases where the person speaking is within say 2 meters of the phone, which seems ok limitation for a phone - ulike for a home device like Alexa).