In this paper a two-stage impulsive noise detection method is proposed to improve the quality of audio signals distorted by impulsive noise. In order to reduce false alarms and missing detection errors, the proposed method first tries to detect whether a frame includes onsets on the basis of inter-frame correlation. Next, hidden Markov model-based maximum likelihood classification is carried out to decide if the onset has occurred from impulsive noise or not. It is shown from performance evaluation that the proposed method achieves higher detection accuracy than with conventional residual domain-based methods under various impulsive noise distributions.

Authors: Jeon, Kwang Myung; Lee, Dong Yun; Park, Nam In; Choi, Myung Kyu; Kim, Hong Kook
Affiliations: Gwangju Institute of Science and Technology (GIST), Gwangju, Korea; Samsung Electronics, Gyeonggi-do, Korea(See document for exact affiliation information.)
AES Convention: 136 (April 2014) Paper Number: 9036
Publication Date: April 25, 2014 Import into BibTeX
Subject: Signal Processing
Permalink: https://www.aes.org/e-lib/browse.cfm?elib=17183

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