Noise Reduction – Overview
When a speech communication device is used in environments with high levels of ambient noise, the noise picked up by the microphone will significantly impair the quality and/or the intelligibility of the transmitted speech signal. In order to get a reliable separation from the noise signal (e.g., engine noise, street noise), noise reduction algorithms have become part of digital speech coding systems recently. They are used for example in mobile communications, in hearing aids and in hands-free devices. Noise reduction systems always provide a tradeoff between speech quality and noise reduction. Hence, the aim is on the one hand to attenuate the noise signal n(k) in the output signal y(k) as much as possible and on the other hand to keep the distortion of the speech signal s(k) as low as possible at the same time.
The problem of noise reduction is illustrated in the following figure:
There are many different ways to perform the noise reduction (e.g., [Vary, Martin-06]). Basically, the solutions can be split in two classes: mono and multi sensor (microphone) systems. Whereas multi sensor systems exploit the spatial properties of speech and noise (e.g., beamforming), a mono sensor system usually relies on the temporal characteristics.
In the following we give an example of a one-channel noise reduction system based on the principles of spectral weighting.