Application of a first-order differential microphone for efficient voice activity detection in a car platform

Handsfree interfaces provide a nice solution to add-on devices in car platforms. However, the amount of acoustic disturbances existing in automotive environments usually prevents satisfactory results. In most of the cases, noise reduction techniques involving a voice activity detector (VAD) are required. Through this paper, a robust microphone array processing technique for speech detection under the influence of noise and reverberation in an automobile environment is proposed. This method applies a simple twomicrophone First Order Differential Microphone in order to estimate the power spectral density of the background perturbations embedded in speech signals. Afterwards, specialized order-statistics filters (OSFs) are applied in order to obtain a consistent speech/non speech decision. The paper also includes a performance evaluation of the algorithm using Aurora3 database recordings. According to our simulation results, the proposed algorithm shows a significantly better performance than standard VADs such as G.729B or ARM and, a slight advantage over other reported methods.