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The importance of video surveillance applications has been increasing with the increase of crime and terrorism. In addition to traditional video cameras, the use of acoustic sensors in surveillance and monitoring applications is also becoming increasingly important. In this paper, we apply High-Order Local Auto-Correlation (HLAC), which has succeeded in video surveillance applications, to extract...
Modern monaural voice and accompaniment separation systems usually consist of two main modules: melody extraction and time-frequency masking. A main distinction between different separation systems lies in what approaches are used for the two modules. Popular techniques for melody extraction include hidden Markov models (HMMs) and non-negative matrix factorization (NMF), and masking includes hard...
Real-world sounds often exhibit time-varying spectral shapes, as observed in the spectrogram of a harpsichord tone or that of a transition between two pronounced vowels. Whereas the standard non-negative matrix factorization (NMF) assumes fixed spectral atoms, an extension is proposed where the temporal activations (coefficients of the decomposition on the spectral atom basis) become frequency dependent...
Time-frequency matrix (TFM) decomposition using non-negative matrix factorization (NMF) has been recently considered as a successful tool for time-frequency (TF) quantification. In this paper, we modify the constraints of traditional cost function of NMF to make the method a better fit for TF quantification, and denote the new method with NMF discriminant base (NMFDB) decomposition. We evaluate the...
Many feature extraction techniques in literature have studied data representation, but most techniques do not explicitly investigate the feature localization aspect. This is one of the first works in which signals have been transformed to matrices using positive time-frequency transform, and matrix decomposition and representation techniques such as PCA, ICA, and NMF have been applied on these matrices...
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