An ultra low power, ultra miniature voice command system based on hidden Markov models
cornu, Destrez, Dufaux, Sheikhzadeh, Brennan · 2002
A real-time HMM-based isolated word recognition system is implemented on an ultra low-power miniature DSP system.The DSP system consumes less than 1 milliWatt, much less than what is considered today as "lowresource".It has a very small footprint and requires only a single hearing aid sized 1 volt battery.The efficient implementation of HMM and MFCC feature extraction algorithms is accomplished through the use of three processing units running concurrently.In addition to the DSP core, an input/output processor creates frames of input speech signals, and a WOLA filterbank unit performs windowing, FFT and vector multiplications.A system evaluation using a vocabulary of 18 words shows a success rate of more than 99%.