878 resultados para ALGOL (Computer program language)


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This paper provides a summary of our studies on robust speech recognition based on a new statistical approach – the probabilistic union model. We consider speech recognition given that part of the acoustic features may be corrupted by noise. The union model is a method for basing the recognition on the clean part of the features, thereby reducing the effect of the noise on recognition. To this end, the union model is similar to the missing feature method. However, the two methods achieve this end through different routes. The missing feature method usually requires the identity of the noisy data for noise removal, while the union model combines the local features based on the union of random events, to reduce the dependence of the model on information about the noise. We previously investigated the applications of the union model to speech recognition involving unknown partial corruption in frequency band, in time duration, and in feature streams. Additionally, a combination of the union model with conventional noise-reduction techniques was studied, as a means of dealing with a mixture of known or trainable noise and unknown unexpected noise. In this paper, a unified review, in the context of dealing with unknown partial feature corruption, is provided into each of these applications, giving the appropriate theory and implementation algorithms, along with an experimental evaluation.

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This paper investigates the problem of seepage under the floor of hydraulic structures considering the compartment of flow that seeps through the surrounding banks of the canal. A computer program, utilizing a finite-element method and capable of handling three-dimensional (3D) saturated–unsaturated flow problems, was used. Different ratios of canal width/differential head applied on the structure were studied. The results produced from the two-dimensional (2D) analysis were observed to deviate largely from that obtained from 3D analysis of the same problem, despite the fact that the porous medium was isotropic and homogeneous. For example, the exit gradient obtained from 3D analysis was as high as 2.5 times its value obtained from 2D analysis. Uplift force acting upwards on the structure has also increased by about 46% compared with its value obtained from the 2D solution. When the canal width/ differential head ratio was 10 or higher, the 3D results were comparable to the 2D results. It is recommended to construct a core of low permeability soil in the banks of canal to reduce the seepage losses, uplift force, and exit gradient.

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This paper considers the separation and recognition of overlapped speech sentences assuming single-channel observation. A system based on a combination of several different techniques is proposed. The system uses a missing-feature approach for improving crosstalk/noise robustness, a Wiener filter for speech enhancement, hidden Markov models for speech reconstruction, and speaker-dependent/-independent modeling for speaker and speech recognition. We develop the system on the Speech Separation Challenge database, involving a task of separating and recognizing two mixing sentences without assuming advanced knowledge about the identity of the speakers nor about the signal-to-noise ratio. The paper is an extended version of a previous conference paper submitted for the challenge.

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This paper presents a new approach to speech enhancement from single-channel measurements involving both noise and channel distortion (i.e., convolutional noise), and demonstrates its applications for robust speech recognition and for improving noisy speech quality. The approach is based on finding longest matching segments (LMS) from a corpus of clean, wideband speech. The approach adds three novel developments to our previous LMS research. First, we address the problem of channel distortion as well as additive noise. Second, we present an improved method for modeling noise for speech estimation. Third, we present an iterative algorithm which updates the noise and channel estimates of the corpus data model. In experiments using speech recognition as a test with the Aurora 4 database, the use of our enhancement approach as a preprocessor for feature extraction significantly improved the performance of a baseline recognition system. In another comparison against conventional enhancement algorithms, both the PESQ and the segmental SNR ratings of the LMS algorithm were superior to the other methods for noisy speech enhancement.

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Damage assessment of structures with a mechanical non linear model demands the representation of seismic action in terms of an accelerogram (dynamic analysis) or a response spectrum (pushover analysis). Stochastic ground motion simulation is largely used in regions where seismic strong-motion records are available in insufficient number. In this work we present a variation of the stochastic finite-fault method with dynamic corner frequency that includes the geological site effects. The method was implemented in a computer program named SIMULSIS that generate time series (accelerograms) and response spectra. The program was tested with the MW= 7.3 Landers earthquake (June 28, 1992) and managed to reproduce its effects. In the present work we used it to reproduce the effects of the 1980’s Azores earthquake (January 1, 1980) in several islands, with different possible local site conditions. In those places, the response spectra are presented and compared with the buildings damage observed.

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One of the aspects of modern agriculture is characterised by a culture without soil (hydroponic cultures). These culture techniques are identified by possessing automatic control systems to control the nutrient solution. In first hydroponic cultures this control was accomplished by “on- off” analog controllers that applied a single control law implemented in hardware. Therefore, the changes of the control law resulted in the change of all interface electronics. In digital control implemented by micro-controllers the alteration of such control law is easily performed by changing only a computer program, leaving untouched all the interface hardware. In this way, the use and substitution of the control strategy is improved, as well, the use of advanced control strategies.

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Trabalho de projeto de mestrado, Educação (Área de Especialização em Educação e Tecnologias Digitais), Universidade de Lisboa, Instituto de Educação, 2014

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Trabalho Final de Mestrado para obtenção do grau de mestre em Engenharia Civil na Área de Especialização em Estruturas

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Trabalho de Projecto para obtenção do grau de Mestre em Engenharia Civil na Área de Especialização de Estruturas

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In the last few years, the number of systems and devices that use voice based interaction has grown significantly. For a continued use of these systems, the interface must be reliable and pleasant in order to provide an optimal user experience. However there are currently very few studies that try to evaluate how pleasant is a voice from a perceptual point of view when the final application is a speech based interface. In this paper we present an objective definition for voice pleasantness based on the composition of a representative feature subset and a new automatic voice pleasantness classification and intensity estimation system. Our study is based on a database composed by European Portuguese female voices but the methodology can be extended to male voices or to other languages. In the objective performance evaluation the system achieved a 9.1% error rate for voice pleasantness classification and a 15.7% error rate for voice pleasantness intensity estimation.

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Trabalho Final de Mestrado para a obtenção do grau de Mestre em Engenharia Civil na Área de Especialização de Estruturas

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Trabalho de Projeto para obtenção do grau de Mestre em Engenharia Civil Área de Especialização em Estruturas

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Dissertação para obtenção do grau de Mestre em Engenharia Civil na Área de Especialização em Estruturas

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Trabalho de Projeto para obtenção do grau de Mestre em Engenharia Civil na Área de Especialização de Estruturas

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Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Civil na Área de Especialização de Estruturas