Effect of noise and distortion in speech on parametric extraction

Parameter or feature extraction from speech signal forms the basis for systems designed for speech recognition, speaker verification, speech bandwidth compression etc. The parameters in general are critically dependent upon the short-time spectrum of speech. The input speech waveform is however, subjected to several types of noises and distortions due to background noise sources, reverberation, close speaking into a microphone, telephone system imperfections etc. These factors modify the spectrum of the speech signal and hence the parameters extracted. Characteristics of common sources of noise and distortion are described in this paper and their effect in shaping the spectrum of speech is discussed. Steps to reduce the influence of some noises while producing speech input to a system are suggested. Methods of normalization of spectral distortions due to noise and the effect of such normalization on parametric extraction are also discussed.