Download PDFOpen PDF in browserCurrent versionOverlapping Acoustic Event Detection via Perceptually Inspired the Holistic-based Representation MethodEasyChair Preprint 2676, version 16 pages•Date: February 15, 2020AbstractA novel dictionary learning approach that utilizes Mel-scale frequency warping in detecting overlapped acoustic events is proposed. The study explored several dictionary learning schemes for improved performance of overlapping acoustic event detection. The structure of NMF for calculating gains of each event was utilized for including in overlapped signal for its low computational load. In this paper, we propose a method of frequency warping for better sound representation, and apply dictionary learning by a holistic-based representation, namely nonnegative K-SVD (NK-SVD) in order to resolve a basis sharing problem raised by part-based representations. We confirm that the proposed method of Mel-scale with NK-SVD delivered significantly better results than the conventional methods. Keyphrases: NMF, Nonnegative K-SVD(NK-SVD), Overlapping Acoustic Event Detection, frequency warping
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