Optimized estimation of spectral parameters for the coding of noisy speech

In this contribution we optimize a speech enhancement preprocessor such that a distortion measure in the line spectral frequency (LSF) domain is minimized. We can thus improve the estimation of spectral parameters of a speech coder when the input signal to the coder is a noisy speech signal. The optimization aims at the maximum noise reduction of the enhancement preprocessor. The average maximum noise reduction characteristic is determined as a function of the speech signal SNR and is approximated by an exponential function. Since LSF parameters are widely used in speech coding the results are applicable to a wide range of speech coders and enhancement preprocessors. We report experimental results for an MMSE log spectral amplitude estimator in conjunction with the new ETSI adaptive multi-rate (AMR) speech coder. We found that the method is most effective for the low bit rate coding modes.