Exploring auditory feedback mechanisms in speech recognition

For many years, automatic speech recognition (ASR) has been built on compressed filter-bank features understood to be a rough model of the cochlea. However, recent understanding, evidenced by oto-acoustic emissions, is that the cochlea is composed of driven oscillators. The Hopf mechanism arising from an oscillator model explains the well known cube-root compression. A bifurcation arises from an inner feedback loop from the outer to inner hair cells. Further, larger feedback loops exist along the efferent path of the auditory nerve, particularly from the olivary complex. The means of combination of these signals is less well understood. In the present study, to the extent to which current compute power allows, we investigate how to incorporate the Hopf mechanism and the olivocochlear feedback mechanisms into ASR. Results show that adding this larger feedback loop appears beneficial for ASR. The results currently have modest implications for ASR, however, perhaps more importantly, such technology could be used to make inference about the biological mechanism.