The problem of speech/music discrimination is a challenging research problem which significantly impacts Automatic Speech Recognition (ASR) performance. This paper proposes new features for the Speech/Music discrimination task. We propose to use a decomposition of the audio signal based on wavelets, which allows a good analysis of non stationary signal like speech or music. We compute different...

A framework for learning optimal dictionaries for simultaneous sparse signal representation and robust class classification is introduced in this paper. This problem for dictionary learning is solved by a class-dependent supervised simultaneous orthogonal matching pursuit, which learns the intra-class structure while increasing the inter-class discrimination, interleaved with an efficient dicti...

We study distance-based classification of human actions and introduce a new metric learning approach based on logistic discrimination for the determination of a low-dimensional feature space of increased discrimination power. We argue that for effective distance-based classification, both the optimal projection space and the optimal class representation should be determined. We qualitatively an...

Saliency mechanisms play an important role when visual recognition must be performed in cluttered scenes. We propose a computational definition of saliency that deviates from existing models by equating saliency to discrimination. In particular, the salient attributes of a given visual class are defined as the features that enable best discrimination between that class and all other classes of ...

A texture discrimination scheme is proposed wherein probability distributions are deployed on a probabilistic manifold for modeling the wavelet statistics of images. We consider the Rao geodesic distance (GD) to the class centroid for texture discrimination in various classification experiments. We compare the performance of GD to class centroid with the Euclidean distance in a similar context,...

An application of artificial neural networks (ANN) for discrimination between natural earthquakes and underground nuclear explosions has been studied using distance corrected spectral data of regional seismic phases. Pn, Pg, and Lg spectra have been analyzed from 83 western U.S. earthquakes and 87 Nevada Test Site explosions recorded at the four broadband seismic stations operated by Lawrence L...

Recent theories posit that adult neurogenesis supports dentate gyrus pattern separation and hence is necessary for some types of discrimination learning. Using an inducible transgenic mouse model, we investigated the contribution of adult-born neurons to spatial and nonspatial touch-screen discriminations of varying levels of difficulty. Arresting neurogenesis caused a modest but statistically ...

Rabbits were trained to discriminate patterns consisting of straight bars and rows of dots of different orientation. It was found that using proximal pattern presentation, at a distance of 5 cm in front of the animal, dot rows of different orientation are not discriminated on the basis of tilt extrapolation, but by the use of regional cues.

The paper describes a novel computational tool for multiple concept learning. Unlike previous approaches, whose major goal is prediction on unseen instances rather than the legibility of the output, our MPD (Maximally Parsimonious Discrimination) program emphasizes the conciseness and intelligibility of the resultant class descriptions, using three intuitive simplicity criteria to this end. We ...