16th Annual Conference of the International Speech Communication Association

Dresden, Germany
September 6-10, 2015

On Optimal Smoothing in Minimum Statistics Based Noise Tracking

Aleksej Chinaev, Reinhold Haeb-Umbach

Universität Paderborn, Germany

Noise tracking is an important component of speech enhancement algorithms. Of the many noise trackers proposed, Minimum Statistics (MS) is a particularly popular one due to its simple parameterization and at the same time excellent performance. In this paper we propose to further reduce the number of MS parameters by giving an alternative derivation of an optimal smoothing constant. At the same time the noise tracking performance is improved as is demonstrated by experiments employing speech degraded by various noise types and at different SNR values.

Full Paper

Bibliographic reference.  Chinaev, Aleksej / Haeb-Umbach, Reinhold (2015): "On optimal smoothing in minimum statistics based noise tracking", In INTERSPEECH-2015, 1785-1789.