Wavelet speech enhancement algorithm using exponential semi-soft mask filtering. Issue 5 (2nd September 2016)

• Record Type: Journal Article
• Authors: Lee, Gihyoun; Dae Na, Sung; Seong, KiWoong; Cho, Jin-Ho; Nam Kim, Myoung
• Is Part Of: Bioengineered. Volume 7:Issue 5(2016)
• Page Start: 352
• Page End: 356
• Publication Date: 2016-09-02
• Subjects: binary mask filtering -- semi-soft filtering -- speech enhancement -- wavelet shrinkage -- wavelet transform; Biomedical engineering -- Periodicals; Biotechnology -- Periodicals; Microbiology -- Periodicals; 660.6
• DOI: 10.1080/21655979.2016.1197617
• Languages: English
• ISSNs: 2165-5987

Abstract

ABSTRACT: In this paper, we propose a new speech enhancement algorithm based on wavelet packet decomposition and mask filtering. In the traditional mask filtering such as ideal binary mask (IBM), the basic idea is to classify speech components as target signal and non-speech components as background noises. However, speech and non-speech components cannot be well separated in target signal and background noise. Therefore, the IBM has residual noise and signal loss. To overcome this problem, the proposed algorithm used semi-soft mask filter to exponentially increase. The semi-soft mask minimizes signal loss and the exponential filter removes residual noise. We performed experiments using various types of speech and noise signals, and experimental results show that the proposed algorithm achieves better performances than the traditional other speech enhancement algorithms.