Leandro Daniel Vignolo

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By means of full wavelet packet decomposition a redundant set of coefficients is obtained. For signal classification it is convenient to find a subset of these coefficients minimizing the error rate of a classifier. A problem arises because of the computational cost of GA solution. This work presents the parallelization of a genetic algorithm by which it is(More)
Some of the most commonly used speech representations, such as mel-frequency cepstral coefficients, incorporate biologically inspired characteristics into artificial systems. Recent advances have been introduced modifying the shape and distribution of the traditional perceptually scaled filterbank, commonly used for feature extraction. Some alternatives to(More)
Mel-frequency cepstral coefficients have long been the most widely used type of speech representation. They were introduced to incorporate biologically inspired characteristics into artificial speech recognizers. Recently, the introduction of new alternatives to the classic mel-scaled filterbank has led to improvements in the performance of phoneme(More)
Active shape models is an adaptive shape-matching technique that has been used for locating facial features in images. However, when a number of features is extracted for each landmark point, distortions caused by noise or illumination, and the dimensionality of the final representation, have a negative impact in the performance of a classifier. In this(More)
Evolutionary algorithms provide flexibility and robustness required to find satisfactory solutions in complex search spaces. This is why they are successfully applied for solving real engineering problems. In this work we propose an algorithm to evolve a robust speech representation, using a dynamic data selection method for reducing the computational cost(More)
The most widely used speech representation is based on the mel-frequency cepstral coefficients, which incorporates biologically inspired characteristics into artificial recognizers. However, the recognition performance with these features can still be enhanced, specially in adverse conditions. Recent advances have been made with the introduction of wavelet(More)
The pervasive development disorders in autism condition lead to impairments in language and social communication. They are evidenced as atypical prosody production, emotion recognition and apraxia, among others communication deficits. This work tackle with the problem of the recognition of pathologies derived from these disorders in children, based on the(More)
Although most of the natural emotions expressed in speech can be clearly identified by humans, automatic classification systems still display significant limitations on this task. Recently, hierarchical strategies have been proposed using different heuristics for choosing the appropriate levels in the hierarchy. In this paper, we propose a method for(More)