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.
(See document for exact affiliation information.)
Click to purchase paper as a non-member or login as an AES member. If your company or school subscribes to the E-Library then switch to the institutional version. If you are not an AES member Join the AES. If you need to check your member status, login to the Member Portal.
