Maximum likelihood noise cancellation with spectral constraints

The estimation of a signal when two observations (signal+noise) are available is addressed. The target application is the enhancement of noisy speech for mobile radio applications. Noises are considered to be spatially decorrelated. A maximum likelihood problem is formulated to estimate the parameters required to cancel the noise, which is solved by the estimate-maximize algorithm. In order to control and enhance this iterative technique, the authors apply spectral constraints (line spectrum pairs) to improve speech quality. Their method is tested on real noisy speech signals recorded in a car. Results relative to the gain on the signal-to-noise ratio and cepstral distances are presented to evaluate the proposed method