Paper Info
Title
On Optimal Smoothing In Minimum Statistics Based Noise Tracking
Abstract
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.
Year
Venue
Keywords
2015
16TH ANNUAL CONFERENCE OF THE INTERNATIONAL SPEECH COMMUNICATION ASSOCIATION (INTERSPEECH 2015), VOLS 1-5
speech enhancement, noise tracking, optimal smoothing
Field
DocType
Citations 
Speech enhancement,BitTorrent tracker,Parametrization,Computer science,Speech recognition,Smoothing,Statistics
Conference
0
PageRank 
References 
Authors
0.34
11
2
Name
Order
Citations
PageRank
Aleksej Chinaev1223.05
Reinhold Haeb-Umbach21487211.71