Picture of neon light reading 'Open'

Discover open research at Strathprints as part of International Open Access Week!

23-29 October 2017 is International Open Access Week. The Strathprints institutional repository is a digital archive of Open Access research outputs, all produced by University of Strathclyde researchers.

Explore recent world leading Open Access research content this Open Access Week from across Strathclyde's many research active faculties: Engineering, Science, Humanities, Arts & Social Sciences and Strathclyde Business School.

Explore all Strathclyde Open Access research outputs...

Adaptive empirical mode decomposition for signal enhancement with application to speech

Chatlani, Navin and Soraghan, J.J. (2008) Adaptive empirical mode decomposition for signal enhancement with application to speech. In: 15th International Conference on Systems, Signals and Image Processing, 2008. IEEE, pp. 101-104. ISBN 978-80-227-2856-0

Full text not available in this repository. Request a copy from the Strathclyde author

Abstract

Speech enhancement is performed in a wide and varied range of instruments and systems. In this paper, a novel approach to signal enhancement using adaptive empirical mode decomposition (SEAEMD) is presented. Spectral analysis of non-stationary signals can be performed by employing techniques such as the STFT and the Wavelet transform, which use predefined basis functions. The empirical mode decomposition (EMD) performs very well in such environments and it decomposes a signal into a finite number of data-adaptive basis functions, called intrinsic mode functions (IMFs). The new SEAEMD system incorporates this multi-resolution approach with adaptive noise cancellation in order to perform signal enhancement on an IMF level. In comparison to the conventional adaptive noise cancellation, the application of SEAEMD to speech gives rise to improved quality and lower level of residual noise.