Enhancement of noisy speech signals: Application to mobile radio communications
This paper deals with the enhancement of noisy speech signals recorded in a car for mobile radio applications. Our concern is the signal estimation when 1 or 2 observations are available; each one is composed of a speech signal, si, and an additive noise n(i) (i = 1, 2). In the case of one microphone, we consider new techniques that capitalize on the aspect of speech perception by focusing on enhancing only the short-time spectral amplitude. A ''modified spectral subtraction'' method is proposed; it uses a frequency-dependent over-estimate of the noise and can be combined with segmentation of the observation. When two microphones are available, in the case of uncorrelated (or slightly correlated) noises, we introduce a new technique based on the coherence function which is used to filter the observations or to determine a speech/noise classification algorithm. Finally, listening tests have been conducted to compare the simplest methods. In the case of stationary noise, the modified spectral subtraction is very promising and in the case of non-stationary and decorrelated noises, the method based on the coherence is more attractive.
spectral subtraction segmentation coherence function noise cancellation