The need to remove or suppress acoustic noise arises in many situations in which the
voice signal originates from a noisy location or is affected by noise over a communication
channel. This Chapter presents an up-to-date coverage of all major noise suppression algorithms
proposed over the past two decades including spectral subtractive algorithms, Wiener filtering,
statistical-model based algorithms and subspace algorithms. It presents a comprehensive
evaluation and comparison of major enhancement algorithms in terms of speech quality and
speech intelligibility. Finally, this hapter concludes with a description of major objective
measures used for predicting the subjective quality and intelligibility of noise-suppressed
speech.
Keywords: Spectral subtractive algorithms, statistical-based speech enhancement, modulation filtering,
subspace methods.
