Improved microphone array design with statistical speaker verification

Abstract

Conventional microphone array implementations aim to lock onto a source with given location and if required, tracking it. It is a challenge to identify the intended source when the location of the source is unknown and interference exists in the same environment. In this study we combine speaker verification and microphone array processing techniques to localize and maximize gain on the intended speaker under the assumption of open acoustic field. We exploit the steering capability of the microphone array for more accurate speaker verification. Our first contribution is a new N-Gram based and computationally efficient feature for detecting an intended speaker. When the source and interference are localized, microphone array can be tuned further to reduce noise and increase the gain. Our second contribution is this integrated algorithm for speaker verification and localization. In the context of this study we developed SharpEar, an open source environment that simulates propagation of sound emanating from multiple sources. Our third and last contribution is this simulation environment, which is open source and available to researchers of the field.