Abstract
Acoustic interferences such as the background noise and reverberation are the major causes of quality degradation in speech communication. During the several decades, a huge number of attempts to reduce the effect of these interferences have been made by employing statistical model based techniques. In the statistical model based techniques, not only the clean speech source but also the background noise and acoustic echo are assumed to be generated from a class of parametric distributions for which there exist efficient methods to estimate the relevant parameters. In this chapter, we review the parametric models and their application to voice activity detection, noise reduction, and echo suppression, which are important preprocessing parts in robust speech communication systems.
Keywords: voice activity detection, noise reduction, echo suppression
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