Clear and effective communication is crucial for the safe operation of aircraft. In helicopters, high levels of noise are generated by the engine, gears, and aerodynamics, which negatively impact speech intelligibility. To address this issue, modern aircraft headsets utilize active noise control (ANC) to reduce noise levels for both the crew and passengers. However, the speech signals captured by these headsets often contain high levels of background noise, thereby hindering internal and external flight communication. This paper introduces a dual microphone dual stage speech enhancement algorithm that combines basic spectral subtraction with a Wiener Filter, enhanced by the a priori and a posteriori signal-to-noise ratio. Audio data from within a helicopter cabin were recorded during a test flight. In a series of simulations, the Wiener Filter implementation is compared to other algorithms based only on spectral subtraction methods. The results are evaluated using established performance measures for speech quality. The Wiener Filter implementation results in the highest speech quality and is, therefore, implemented on an FPGA-platform for validation in a laboratory experiment. The simulations and measurements demonstrate significant improvements in speech quality and, consequently, enhance speech intelligibility using the proposed method.

This content is only available via PDF.