Noise suppression using non-linear speech model

Pintér, István (2007) Noise suppression using non-linear speech model. Pollack Periodica, 2 (Supple). pp. 121-133. ISSN 1788-1994

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Abstract

Noise suppression has been a long-standing problem in digital speech processing. For average signal-to-noise ratio (SNR) and stationary noise there are commercially available software products or equipment. Therefore, the subject of the recent research is the enhancement of noisy speech in case of non-stationary noise. The noise suppression algorithm, presented in this paper, is based on dimension-embedding, and separates speech from noise in the transformed domain. The algorithm has been tested on several noisy versions of a Hungarian sentence using three different noise-types and seven different SNRs. The gains achieved correspond to the published data.

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