Itt Corporation

Itt Manufacturing Enterprises, Inc.

Jack E Porter

Steven F Boll

Alan L Higgins

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 f,; 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 N,associated with the particular frequency; determining a channel frequency response C,associated with the particular frequency by determining a geometric mean over all the spectral samples having magnitude exceeding the noise threshold N,; subtracting from each of the magnitudes of the N point spectral samples the noise threshold N,to provide a noise suppressed sample sequence; applying blind deconvolution to the noise suppressed samples; transforming the deconvolved noise suppressed sampled sequence to a temporal representation; shifting the temporal sample sequence in time by a predetermined amount; and adding the time shifted temporal samples over a period corresponding to the predetermined temporal window to provide a suppressed noise voice signal.

Noise suppression and channel equalization preprocessor for speech and speaker recognizers: method and apparatus

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.

Apparatus and methods for the selective addition of noise to templates

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.

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San Diego, CA, United States of America

Jack E Porter