951 resultados para Visual Speech Recognition, Multiple Views, Frontal View, Profile View
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ARAUJO, Márcio V. ; ALSINA, Pablo J. ; MEDEIROS, Adelardo A. D. ; PEREIRA, Jonathan P.P. ; DOMINGOS, Elber C. ; ARAÚJO, Fábio M.U. ; SILVA, Jáder S. . Development of an Active Orthosis Prototype for Lower Limbs. In: INTERNATIONAL CONGRESS OF MECHANICAL ENGINEERING, 20., 2009, Gramado, RS. Proceedings… Gramado, RS: [s. n.], 2009
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Variability management is one of the major challenges in software product line adoption, since it needs to be efficiently managed at various levels of the software product line development process (e.g., requirement analysis, design, implementation, etc.). One of the main challenges within variability management is the handling and effective visualization of large-scale (industry-size) models, which in many projects, can reach the order of thousands, along with the dependency relationships that exist among them. These have raised many concerns regarding the scalability of current variability management tools and techniques and their lack of industrial adoption. To address the scalability issues, this work employed a combination of quantitative and qualitative research methods to identify the reasons behind the limited scalability of existing variability management tools and techniques. In addition to producing a comprehensive catalogue of existing tools, the outcome form this stage helped understand the major limitations of existing tools. Based on the findings, a novel approach was created for managing variability that employed two main principles for supporting scalability. First, the separation-of-concerns principle was employed by creating multiple views of variability models to alleviate information overload. Second, hyperbolic trees were used to visualise models (compared to Euclidian space trees traditionally used). The result was an approach that can represent models encompassing hundreds of variability points and complex relationships. These concepts were demonstrated by implementing them in an existing variability management tool and using it to model a real-life product line with over a thousand variability points. Finally, in order to assess the work, an evaluation framework was designed based on various established usability assessment best practices and standards. The framework was then used with several case studies to benchmark the performance of this work against other existing tools.
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ARAUJO, Márcio V. ; ALSINA, Pablo J. ; MEDEIROS, Adelardo A. D. ; PEREIRA, Jonathan P.P. ; DOMINGOS, Elber C. ; ARAÚJO, Fábio M.U. ; SILVA, Jáder S. . Development of an Active Orthosis Prototype for Lower Limbs. In: INTERNATIONAL CONGRESS OF MECHANICAL ENGINEERING, 20., 2009, Gramado, RS. Proceedings… Gramado, RS: [s. n.], 2009
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While humans can easily segregate and track a speaker's voice in a loud noisy environment, most modern speech recognition systems still perform poorly in loud background noise. The computational principles behind auditory source segregation in humans is not yet fully understood. In this dissertation, we develop a computational model for source segregation inspired by auditory processing in the brain. To support the key principles behind the computational model, we conduct a series of electro-encephalography experiments using both simple tone-based stimuli and more natural speech stimulus. Most source segregation algorithms utilize some form of prior information about the target speaker or use more than one simultaneous recording of the noisy speech mixtures. Other methods develop models on the noise characteristics. Source segregation of simultaneous speech mixtures with a single microphone recording and no knowledge of the target speaker is still a challenge. Using the principle of temporal coherence, we develop a novel computational model that exploits the difference in the temporal evolution of features that belong to different sources to perform unsupervised monaural source segregation. While using no prior information about the target speaker, this method can gracefully incorporate knowledge about the target speaker to further enhance the segregation.Through a series of EEG experiments we collect neurological evidence to support the principle behind the model. Aside from its unusual structure and computational innovations, the proposed model provides testable hypotheses of the physiological mechanisms of the remarkable perceptual ability of humans to segregate acoustic sources, and of its psychophysical manifestations in navigating complex sensory environments. Results from EEG experiments provide further insights into the assumptions behind the model and provide motivation for future single unit studies that can provide more direct evidence for the principle of temporal coherence.
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In this thesis, we propose several advances in the numerical and computational algorithms that are used to determine tomographic estimates of physical parameters in the solar corona. We focus on methods for both global dynamic estimation of the coronal electron density and estimation of local transient phenomena, such as coronal mass ejections, from empirical observations acquired by instruments onboard the STEREO spacecraft. We present a first look at tomographic reconstructions of the solar corona from multiple points-of-view, which motivates the developments in this thesis. In particular, we propose a method for linear equality constrained state estimation that leads toward more physical global dynamic solar tomography estimates. We also present a formulation of the local static estimation problem, i.e., the tomographic estimation of local events and structures like coronal mass ejections, that couples the tomographic imaging problem to a phase field based level set method. This formulation will render feasible the 3D tomography of coronal mass ejections from limited observations. Finally, we develop a scalable algorithm for ray tracing dense meshes, which allows efficient computation of many of the tomographic projection matrices needed for the applications in this thesis.
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This work focuses in the formal and technical analysis of some aspects of a constructed language. As a first part of the work, a possible coding for the language will be studied, emphasizing the pre x coding, for which an extension of the Hu man algorithm from binary to n-ary will be implemented. Because of that in the language we can't know a priori the frequency of use of the words, a study will be done and several strategies will be proposed for an open words system, analyzing previously the existing number of words in current natural languages. As a possible upgrade of the coding, we'll take also a look to the synchronization loss problem, as well as to its solution: the self-synchronization, a t-codes study with the number of possible words for the language, as well as other alternatives. Finally, and from a less formal approach, several applications for the language have been developed: A voice synthesizer, a speech recognition system and a system font for the use of the language in text processors. For each of these applications, the process used for its construction, as well as the problems encountered and still to solve in each will be detailed.
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Almost 10 years after Childhood and Society (Palgrave, 2nd edn, 2011), Michael Wyness, an associate professor of childhood studies at the University of Warwick, now brings to print a short yet broad introduction to the study of childhood. In particular, this book discusses multiple views about childhood, a concept that for the past two decades has been contested within social sciences’ critical theorizing. On the back cover of the book, William A Corsaro and Alan Prout, well-known scholars from the field, are unanimous in recognizing the value of this new contribution in childhood studies. The interested and attentive reader should not be indifferent to their words and judgment; Wyness’s Childhood is a ‘gem,’ according to Corsaro.
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Dissertação de Mestrado, Marketing, Faculdade de Economia, Universidade do Algarve, 2016
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Early intervention is the key to spoken language for hearing impaired children. A severe hearing loss diagnosis in young children raises the urgent question on the optimal type of hearing aid device. As there is no recent data on comparing selection criteria for a specific hearing aid device, the goal of the Hearing Evaluation of Auditory Rehabilitation Devices (hEARd) project (Coninx & Vermeulen, 2012) evolved to collect and analyze interlingually comparable normative data on the speech perception performances of children with hearing aids and children with cochlear implants (CI). METHOD: In various institutions for hearing rehabilitation in Belgium, Germany and the Netherlands the Adaptive Auditory Speech Test AAST was used in the hEARd project, to determine speech perception abilities in kindergarten and school aged hearing impaired children. Results in the speech audiometric procedures were matched to the unaided hearing loss values of children using hearing aids and compared to results of children using CI. 277 data sets of hearing impaired children were analyzed. Results of children using hearing aids were summarized in groups as to their unaided hearing loss values. The grouping was related to the World Health Organization’s (WHO) grading of hearing impairment from mild (25–40 dB HL) to moderate (41–60 dB HL), severe (61-80 dB HL) and profound hearing impairment (80 dB HL and higher). RESULTS: AAST speech recognition results in quiet showed a significantly better performance for the CI group in comparison to the group of profoundly impaired hearing aid users as well as the group of severely impaired hearing aid users. However the CI users’ performances in speech perception in noise did not vary from the hearing aid users’ performances. Within the collected data analyses showed that children with a CI show an equivalent performance on speech perception in quiet as children using hearing aids with a “moderate” hearing impairment.
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To recognize a previously seen object, the visual system must overcome the variability in the object's appearance caused by factors such as illumination and pose. Developments in computer vision suggest that it may be possible to counter the influence of these factors, by learning to interpolate between stored views of the target object, taken under representative combinations of viewing conditions. Daily life situations, however, typically require categorization, rather than recognition, of objects. Due to the open-ended character both of natural kinds and of artificial categories, categorization cannot rely on interpolation between stored examples. Nonetheless, knowledge of several representative members, or prototypes, of each of the categories of interest can still provide the necessary computational substrate for the categorization of new instances. The resulting representational scheme based on similarities to prototypes appears to be computationally viable, and is readily mapped onto the mechanisms of biological vision revealed by recent psychophysical and physiological studies.
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A persistent issue of debate in the area of 3D object recognition concerns the nature of the experientially acquired object models in the primate visual system. One prominent proposal in this regard has expounded the use of object centered models, such as representations of the objects' 3D structures in a coordinate frame independent of the viewing parameters [Marr and Nishihara, 1978]. In contrast to this is another proposal which suggests that the viewing parameters encountered during the learning phase might be inextricably linked to subsequent performance on a recognition task [Tarr and Pinker, 1989; Poggio and Edelman, 1990]. The 'object model', according to this idea, is simply a collection of the sample views encountered during training. Given that object centered recognition strategies have the attractive feature of leading to viewpoint independence, they have garnered much of the research effort in the field of computational vision. Furthermore, since human recognition performance seems remarkably robust in the face of imaging variations [Ellis et al., 1989], it has often been implicitly assumed that the visual system employs an object centered strategy. In the present study we examine this assumption more closely. Our experimental results with a class of novel 3D structures strongly suggest the use of a view-based strategy by the human visual system even when it has the opportunity of constructing and using object-centered models. In fact, for our chosen class of objects, the results seem to support a stronger claim: 3D object recognition is 2D view-based.
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BACKGROUND: In order to maintain the most comprehensive structural annotation databases we must carry out regular updates for each proteome using the latest profile-profile fold recognition methods. The ability to carry out these updates on demand is necessary to keep pace with the regular updates of sequence and structure databases. Providing the highest quality structural models requires the most intensive profile-profile fold recognition methods running with the very latest available sequence databases and fold libraries. However, running these methods on such a regular basis for every sequenced proteome requires large amounts of processing power.In this paper we describe and benchmark the JYDE (Job Yield Distribution Environment) system, which is a meta-scheduler designed to work above cluster schedulers, such as Sun Grid Engine (SGE) or Condor. We demonstrate the ability of JYDE to distribute the load of genomic-scale fold recognition across multiple independent Grid domains. We use the most recent profile-profile version of our mGenTHREADER software in order to annotate the latest version of the Human proteome against the latest sequence and structure databases in as short a time as possible. RESULTS: We show that our JYDE system is able to scale to large numbers of intensive fold recognition jobs running across several independent computer clusters. Using our JYDE system we have been able to annotate 99.9% of the protein sequences within the Human proteome in less than 24 hours, by harnessing over 500 CPUs from 3 independent Grid domains. CONCLUSION: This study clearly demonstrates the feasibility of carrying out on demand high quality structural annotations for the proteomes of major eukaryotic organisms. Specifically, we have shown that it is now possible to provide complete regular updates of profile-profile based fold recognition models for entire eukaryotic proteomes, through the use of Grid middleware such as JYDE.
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Two experiments examine the effect on an immediate recall test of simulating a reverberant auditory environment in which auditory distracters in the form of speech are played to the participants (the 'irrelevant sound effect'). An echo-intensive environment simulated by the addition of reverberation to the speech reduced the extent of 'changes in state' in the irrelevant speech stream by smoothing the profile of the waveform. In both experiments, the reverberant auditory environment produced significantly smaller irrelevant sound distraction effects than an echo-free environment. Results are interpreted in terms of changing-state hypothesis, which states that acoustic content of irrelevant sound, rather than phonology or semantics, determines the extent of the irrelevant sound effect (ISE). Copyright (C) 2007 John Wiley & Sons, Ltd.
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Mode of access: Internet.