Laser interferometric characterization of a vibrating speaker system

An experiment that combines opto-mechanical and electrical measurements for the characterization of a loudspeaker is presented. We describe a very simple laser vibrometer for evaluating the amplitude of the vibration (displacement) of the speaker cone. The setup is essentially a Michelson-type interferometer operated by an inexpensive semiconductor laser (diode laser). It is shown that the simultaneous measurements of three amplitudes (displacement, electrical current, and applied voltage), as functions of the frequency of vibration, allow us to characterize the speaker system. The experiment is easy to perform, and it demonstrates several useful concepts of optics, mechanics, and electricity, allowing, students to gain an intuitive physical insight into the relations between mathematical models and, an actual speaker system. (C) 2003 American Association of Physics Teachers.

Aircraft interior failure pattern recognition utilizing text mining and neural networks

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Discurso de paraninfo

O presente texto é o discurso de paraninfo pronunciado para os formandos da turma de 2001 da Faculdade de Filosofia e Ciências da Universidade Estadual Paulista, Campus de Marília/SP. Constitui-se em pequena reflexão sobre o momento da formatura, a passagem para a vida profissional e os problemas mais candentes que a vida acadêmica enfrenta hoje no Brasil.

Pattern recognition theory in nonlinear signal processing

A body of research has developed within the context of nonlinear signal and image processing that deals with the automatic, statistical design of digital window-based filters. Based on pairs of ideal and observed signals, a filter is designed in an effort to minimize the error between the ideal and filtered signals. The goodness of an optimal filter depends on the relation between the ideal and observed signals, but the goodness of a designed filter also depends on the amount of sample data from which it is designed. In order to lessen the design cost, a filter is often chosen from a given class of filters, thereby constraining the optimization and increasing the error of the optimal filter. To a great extent, the problem of filter design concerns striking the correct balance between the degree of constraint and the design cost. From a different perspective and in a different context, the problem of constraint versus sample size has been a major focus of study within the theory of pattern recognition. This paper discusses the design problem for nonlinear signal processing, shows how the issue naturally transitions into pattern recognition, and then provides a review of salient related pattern-recognition theory. In particular, it discusses classification rules, constrained classification, the Vapnik-Chervonenkis theory, and implications of that theory for morphological classifiers and neural networks. The paper closes by discussing some design approaches developed for nonlinear signal processing, and how the nature of these naturally lead to a decomposition of the error of a designed filter into a sum of the following components: the Bayes error of the unconstrained optimal filter, the cost of constraint, the cost of reducing complexity by compressing the original signal distribution, the design cost, and the contribution of prior knowledge to a decrease in the error. The main purpose of the paper is to present fundamental principles of pattern recognition theory within the framework of active research in nonlinear signal processing.

On the determination of epsilon during discriminative GMM training

Discriminative training of Gaussian Mixture Models (GMMs) for speech or speaker recognition purposes is usually based on the gradient descent method, in which the iteration step-size, ε, uses to be defined experimentally. In this letter, we derive an equation to adaptively determine ε, by showing that the second-order Newton-Raphson iterative method to find roots of equations is equivalent to the gradient descent algorithm. © 2010 IEEE.

Improving face recognition with multispectral fusion and support vector machines

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Folhetins do século XIX: uma prática de leitura apaixonada

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Marcas de influência do echúwabo no português de Moçambique: a questão dos verbos nas redes sociais

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Análise entoacional acústica e auditiva de alguns enunciados do português brasileiro

The main goal of this work is the analysis of theoretical and methodological aspects of speech melody variation (intonation), with special reference to the pronunciation of one speaker. In order to carry on this study, different types of sentences (declarative, questions, etc.) and the intonational focus as well as the speaker‟s attitude (irony, emphasis, etc.) were observed and analyzed with special acoustic software (PRAAT) and with an auditory analysis of a text read by the subject. The aim of this work is to verify whether the acoustic analysis matches with the auditory perception phonetically, according to M.A.K. Halliday‟s methodology, following Cagliari (2007), who adapted Halliday‟s model to describe the intonation of Portuguese

Reconhecimento de voz para aplicações em automação implementado em FPGA

In many movies of scientific fiction, machines were capable of speaking with humans. However mankind is still far away of getting those types of machines, like the famous character C3PO of Star Wars. During the last six decades the automatic speech recognition systems have been the target of many studies. Throughout these years many technics were developed to be used in applications of both software and hardware. There are many types of automatic speech recognition system, among which the one used in this work were the isolated word and independent of the speaker system, using Hidden Markov Models as the recognition system. The goals of this work is to project and synthesize the first two steps of the speech recognition system, the steps are: the speech signal acquisition and the pre-processing of the signal. Both steps were developed in a reprogrammable component named FPGA, using the VHDL hardware description language, owing to the high performance of this component and the flexibility of the language. In this work it is presented all the theory of digital signal processing, as Fast Fourier Transforms and digital filters and also all the theory of speech recognition using Hidden Markov Models and LPC processor. It is also presented all the results obtained for each one of the blocks synthesized e verified in hardware

Paixão, mito e formas de vida em textos publicitários

The passion, understood by Aristotle, as a contingency which causes a change in the essence of the subject, was object of research of the Greek philosopher as rhetorical strategy used by the speaker to touch its listeners. The greimasian semiotics, enlarging the concept of Aristotle’s passion, understands it as the soul states of a subject that can be gathered form the analysis of a text. Reflections towards the passion discursivization and its persuasion effects in advertisements lead us to establish the relationships between passion, myth and ways of life.

Compreensão e produção oral de sentenças em crianças com deficiência auditiva pré-lingual usuárias de implante coclear

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

A escrita dialógica: investigando o relacionamento do sujeito com o próprio texto

Pós-graduação em Letras - FCLAR

Pertencer e deslocar virtualmente: Teletandem como espaço antropofágico

Pós-graduação em Estudos Linguísticos - IBILCE