Abstract: A speech analyzing stage (12) and a method for analyzing a speech signal is described. The speech analyzing stage (12) is part of an automatic speech recognition system (10) and is adapted for analyzing in the spectral domain a speech signal sampled at one of at least two different system sampling rates. The speech analyzing stage (12) comprises a first spectral analyzer (18a) for analyzing the speech signal up to a first frequency (flowest) which is preferably derived from the lowest system sampling rate (2×flowest) and a second spectral analyzer (18b) for analyzing the speech signal at least above the first frequency (flowest).

Abstract: The present invention relates to a method and an apparatus for a robust feature extraction for speech recognition in a noisy environment, wherein the speech signal is segmented and is characterized by spectral components. The speech signal is splitted into a number of short term spectral components in L subbands, with L=1, 2, . . . and a noise spectrum from segments that only contain noise is estimated. Then a spectral subtraction of the estimated noise spectrum from the corresponding short term spectrum is performed and a probability for each short term spectrum component to contain noise is calculated. Finally these spectral component of each short-term spectrum, having a low probability to contain speech are interpolated in order to smooth those short-term, spectra that only contain noise. With the interpolation the spectral components containing noise are interpolated by reliable spectral speech components that could be found in the neighborhood.