In this paper, we propose a Bark-scale shift based piecewise nonlinear warping function for speaker normalization, and a joint frequency discontinuity and energy attenuation detection algorithm to estimate the second subglottal resonance (Sg2). We then apply Sg2 for rapid speaker normalization. Experimental results on children’s speech recognition show that the proposed nonlinear warping functi...

Dynamic time warping constitutes a major tool for analyzing time series. In particular, computing a mean series of a given sample of series in dynamic time warping spaces (by minimizing the Fréchet function) is a challenging computational problem, so far solved by several heuristic, inexact strategies. We spot several inaccuracies in the literature on exact mean computation in dynamic time warp...

In this study we have developed a digital guitar body mode modulation technique where the modulation can be controlled through one driving parameter. The filtering and modulation is done with frequency-warped recursive filters that have been implemented in real-time on a modern DSP processor. By changing the warping parameter the perceived size of the body can be controlled, by a pedal or autom...

This paper establishes a new coherent framework to extend the class of unitary warping operators to the case of discrete–time sequences. Providing some a priori considerations on signals, we show that the class of discrete–time warping operators finds a natural description in linear shift– invariant spaces. On such spaces, any discrete–time warping operator can be seen as a non–uniform weighted...

This thesis explores performance criteria adequate to validate simulation models. An overview on the most widely performance criteria used in literature is firstly provided. The thesis proceeds with the proposal of two new criteria that assess the distortion of the warping path obtained after applying the Dynamic Time Warping algorithm: the Warping Path Distortion (WPD) and the Percentage Warpi...

A method is proposed to improve any temporal pattern recognition system by time warping each pattern before presentation to the recognition system. The time warping function for a pattern is generated by repeated local application of a neural network to sections of the pattern. The output of this neural network is the slope of the warping function, and the internal weight parameters are trained...

Warping can be used to reduce interindividual structural variations of 3D image datasets of brains by generating a standard brain and subsequent matching of individual datasets to this reference system. Point-based warping uses structural information (landmarks) to construct the spatial correspondence between the datasets. For this we compare the performance of three landmark detection algorith...