This study investigates the variance and invariance in speech rate as a reflection of conceptual planning and cognitive rhythm. A four-frame comic strip was used to elicit speech and low-pass smoothing was done afterwards to filter out high frequency noise. Results showed that subjects invariably planned narration in terms of story plots. Variance lies in the way subjects synchronize planning a...

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Joint time-frequency distributions represent the energy or intensity of signal simultaneously in time and frequency. In this paper we introduce a smoothed version of the method denoted as S-method (SM) [18]. It is shown that it is an effective tool for representation of speech signals disturbed by noise. As a consequence, it can be efficiently applied to time-variant filter problems, as they oc...

The theory and practice of log-domain filter design has reached the point where it is possible to incorporate log-domain filter structures into large current-mode VLSI systems. We report on interface circuits used to implement a current-mode frontend filterbank and feature extractor for acoustic pattern recognition. These circuits maintain a log-domain structure, acting on the unexpanded filter...

Median filter is quite effective in recovering the images confounded by salt and pepper noise. It discards outliers (impulses) effectively, but it fails to provide adequate smoothing for images corrupted with non-impulse noise. In this paper, two nonlinear techniques for image filtering, namely, New Filter I and New Filter II are proposed based on a nonlinear high-pass filter algorithm. New Fil...

Many patch-based image denoising algorithms can be formulated as applying a smoothing filter to the noisy image. Expressed as matrices, the smoothing filters must be row normalized so that each row sums to unity. Surprisingly, if we apply a column normalization before the row normalization, the performance of the smoothing filter can often be significantly improved. Prior works showed that such...

Recently, multi-level stress assessment has become an active research subject. In this context, researchers typically develop models based on machine learning classifiers and features extracted from biosignals like electrocardiogram (ECG) or electroencephalogram (EEG). For that purpose, EEG power spectral density (PSD) is a recurrent feature owing to its high responsiveness remarkable performan...