Noise reduction based on spectral change

A noise reduction algorithm is designed for the aural enhancement of short-duration wideband signals. The signal of interest contains components possibly only a few milliseconds in duration and corrupted by a nonstationary noise background. The essence of the enhancement technique is a Wiener filter that uses a desired signal spectrum whose estimation adapts to the “degree of stationarity” of the measured signal. The degree of stationarity is derived from a short-time spectral derivative measurement, motivated by sensitivity of biological systems to-spectral change. Adaptive filter design tradeoffs are described, reflecting the accuracy of signal attack, background fidelity, and perceptual quality of the desired signal. Residual representations for binaural presentation are also considered