Abstract: A method for performing noise suppression and channel equalization of a noisy voice signal comprising the steps of sampling the noisy voice signal at a predetermined sampling rate fs; segmenting the sampled voice signal into a plurality of frames having a predetermined number of samples per frame, over a predetermined temporal window; generating an N-point spectral sample representation of each of the sample signal frames; determining the magnitude of each of the N-point spectral samples and generating a histogram of the energy associated with each of the N-point spectral samples at a particular frequency; detecting a peak amplitude of the histogram which corresponds to a noise threshold Nf associated with the particular frequency; determining a channel frequency response Cf associated with the particular frequency by determining a geometric mean over all the spectral samples having magnitude exceeding the noise threshold Nf; subtracting from each of the magnitudes of the N point spectral samples the noise th

Abstract: To improve the recognition of incoming speech signals in noise, the prestored templates of noise-free speech are modified to have the estimated spectral values of noise and the same signal-to-noise ratio as the incoming signal.

Abstract: A method and apparatus for noise suppression for speech recognition systems which employs the principle of a least means square estimation which is implemented with conditional expected values. Essentially, according to this method, one computes a series of optimal estimators which estimators and their variances are then employed to implement a noise immune metric. This noise immune metric enables the system to substitute a noisy distance with an expected value which value is calculated according to combined speech and noise data which occurs in the bandpass filter domain. Thus the system can be used with any set of speech parameters and is relatively independent of a specific speech recognition apparatus structure.