METHOD AND MEANS FOR A ROBUST FEATURE EXTRACTION FOR SPEECH RECOGNITION

摘要

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 components 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.