Circular microphone array beamforming to improve speech recognition for virtual agents

Abstract

Under funding from an NIH NIDCD SBIR phase 1 and phase 2 grant, mh acoustics built a 16-element concentric circular microphone array using both analog and digital MEMS microphones. The circular microphone array design was trademarked as the EigenEar® microphone array and the unique beamforming processing is covered by U.S. patent 8903106. The presentation aims at showing that a circular third-order differential beamformer is capable of improving the recognition rate of popular voice recognition services used by a number of commercially available virtual assistants. These services offer an API to a client allowing speech data to be uploaded, analyzed, and returned in text form to the client. Experiments were done to compare the recognition accuracy from two separate audio streams. The EigenEar microphone array has two output channels and one channel contained the output of one omnidirectional microphone in the array and the other channel contained the output of the beamformer. The two audio streams are time synchronous so both streams presented to the virtual assistant are time aligned. The talk will describe the EigenEar circular microphone array and how the experiment was setup and the ASR results obtained from the virtual agents.