Low latency and tight resources viseme recognition from speech using an artificial neural network

We present a speech driven real-time viseme recognition system based on Artificial Neural Network (ANN). A Multi-Layer Perceptron (MLP) is used to provide a light and responsive framework, adapted to the final application (i.e., the animation of the lips of an avatar on multi-task platforms with embedded resources and latency constraints). Several improvements of this system are studied such as data selection, network size, training set size, or choice of the best acoustic unit to recognize. All variants are compared to a baseline system, and the combined improvements achieve a recognition rate of 64.3% for a set of 18 visemes and 70.8% for 9 visemes. We then propose a tradeoff system between the recognition performance, the resource requirements and the latency constraints. A scalable method is also described.Ce rapport présente un système de reconnaissance de visèmes à partir du signal de parole utilisant un réseau de neurones artificiels et capable de fonctionner en temps réel. Un Multi-Layer Perceptron (MLP) permet d'obtenir une méthode rapide et légère adaptée à l'application finale (i.e., l'animation des lèvres d'un avatar par une plateforme multitâche de type set-top-box avec des contraintes de ressources et de latence). Plusieurs améliorations de ce système sont également présentées telles que la sélection des données d'apprentissage, la taille du réseau, la taille de la base d'apprentissage ou encore le choix de l'unité acoustique à reconnaître. Toutes ces variantes sont comparées au système de base. La combinaison de toutes ces améliorations permet d'atteindre un taux de reconnaissance de 64.3% pour un jeu de 18 visèmes et 70.8% pour 9 visèmes. Nous proposons ensuite un système faisant le compromis entre performance, besoin en ressources et latence. Une variante adaptable (scalable) est aussi décrite

Choosing an Optimal Neural Network Size to Aid a Search through a Large Image Database

In this paper a fast method of selecting a neural network architecture for pattern recognition tasks is presented. We demonstrate that our proposed method of selecting both input features and hidden neurons avoids the pitfalls exhibited by other methods reported in the literature. It is also shown that the resulting network architecture is extremely lean while at the same time significantly improving the network performance. The resulting solution provides a very useful tool which is now being incorporated in the operations system used for large image database surveys. 1 Introduction Pattern recognition neural networks are used to obtain a non-linear function mapping between the input pattern space and the output decision space. In an #-layer feed-forward network (in which the inputs are not considered a layer) there are # # # # ### ## ### #### # free parameters (weights and biases) that try to model this mapping, where # # is the number of units in layer #. For example, a ..

Identification and tracking of marine objects for collision risk estimation.

With the advent of modem high-speed passenger ferries and the general increase in maritime traffic, both commercial and recreational, marine safety is becoming an increasingly important issue. From lightweight catamarans and fishing trawlers to container ships and cruise liners one question remains the same. Is anything in the way? This question is addressed in this thesis. Through the use of image processing techniques applied to video sequences of maritime scenes the images are segmented into two regions, sea and object. This is achieved using statistical measures taken from the histogram data of the images. Each segmented object has a feature vector built containing information including its size and previous centroid positions. The feature vectors are used to track the identified objects across many frames. With information recorded about an object's previous motion its future motion is predicted using a least squares method. Finally a high-level rule-based algorithm is applied in order to estimate the collision risk posed by each object present in the image. The result is an image with the objects identified by the placing of a white box around them. The predicted motion is shown and the estimated collision risk posed by that object is displayed. The algorithms developed in this work have been evaluated using two previously unseen maritime image sequences. These show that the algorithms developed here can be used to estimate the collision risk posed by maritime objects

Experiência Profissionalizante na vertente de Farmácia Comunitária, Hospitalar e Investigação

O estágio curricular, realizado no final do Mestrado Integrado em Ciências Farmacêuticas, apresenta-se como a oportunidade de aplicar os conhecimentos adquiridos ao longo dos 5 anos de estudo, constituindo uma importante aproximação à prática profissional e uma oportunidade de contato com as tarefas e atividades desenvolvidas pelo Farmacêutico. De forma igual à realização do estágio curricular, este relatório encontra-se organizado em três partes distintas: a primeira referente à componente de investigação desenvolvida, a segunda referente ao estágio em Farmácia Comunitária, e por último, a terceira referente ao estágio em Farmácia Hospitalar. No primeiro capítulo encontra-se a componente de investigação desenvolvida, intitulada: "Predição in silico da permeabilidade intrínseca determinada pelo ensaio in vitro Double-Sink PAMPA utilizando redes neuronais artificiais". Os ensaios in vitro são imprescindíveis na descoberta e desenvolvimento de novos fármacos. O PAMPA, Parallel Artificial Membrane Permeability Assay, é um exemplo de grande utilidade nos processos de screening in vitro da permeabilidade intestinal, permitindo prioritizar as moléculas com propriedades mais favoráveis. Apesar da utilidade dos modelos in vitro, é hoje consensual a necessidade do desenvolvimento e aplicação prévia de modelos in silico nas fases iniciais de descoberta de fármacos. Os ensaios in silico, embora menos exatos que os in vitro, possibilitam um screening rápido, a baixo custo, de milhares de moléculas, permitindo selecionar as mais promissoras para posterior avaliação in vitro. Neste âmbito, as redes neuronais artificiais têm vindo a assumir um papel relevante na avaliação farmacológico in silico. Desta forma, com este trabalho pretende-se desenvolver um modelo computacional (in silico) para a predição da permeabilidade intrínseca (Po) de compostos utilizando redes neuronais artificiais (ANNs), construído com observações feitas em 273 moléculas, utilizando apenas descritores calculados in silico. No segundo capítulo encontra-se descrito o estágio curricular em Farmácia Comunitária. Este estágio foi realizado na Farmácia São Cosme, na Covilhã, entre os dias 4 de fevereiro e 3 de maio de 2013. Sob a orientação do Dr. Carlos Tavares e toda a equipa presente na Farmácia, foi me dada a oportunidade de integrar uma equipa de trabalho e acompanhar e experienciar todas as atividades desenvolvidas pelo Farmacêutico neste âmbito profissional. Com este relatório pretende-se descrever o funcionamento de uma Farmácia Comunitária, bem como as tarefas e responsabilidades do farmacêutico nesta. Por último, no terceiro capítulo encontra-se descrito o estágio curricular em Farmácia Hospitalar, realizado nos Serviços Farmacêuticos Hospitalares do Centro Hospitalar Cova da Beira, entre os dias 6 de maio e 21 de junho de 2013. Sob orientação da Prof.ª Olímpia Fonseca e colegas presentes nas diversas áreas, tive a oportunidade de participar nas diversas tarefas e atividades desenvolvidas neste serviço. Com este relatório pretende-se assim descrever as atividades que acompanhei e realizei, bem como as competências técnicas que adquiri.The final traineeship, held at the end of the Pharmaceutical Sciences master's degree program, presents itself as an opportunity to apply the knowledge gained over the five years of study, as well as it is an important approach to the professional practice and a chance to observe the tasks and activities developed by the Pharmacist. Similarly to the traineeship, this report is organized into three distinct parts: the first related wit h the research component, the second related with Community Pharmacy traineeship, and lastly, the third related with the Hospital Pharmacy traineeship. The first chapter describes the research component developed, entitled: "In silico prediction of the in vitro intrinsic permeability determined in Double-Sink PAMPA by using artificial neural networks". In vitro assays are essential in the discovery and development of new drugs. PAMPA, Parallel Artificial Membrane Permeability Assay, is an example of great interest for screening of intestinal permeability, allowing the prioritization of molecules with more favorable properties. Despite the usefulness of in vitro models, it is now generally agreed to the need for development and prior application of in silico model in the early stages of drug discovery. In silico assays, although less accurate than the in vitro assays, are powerful tools for a rapid virtual screening of thousands of compounds at low cost, allowing to select the most promising for further in vitro evaluation. In this context, artificial neural networks have come to play a relevant role in the in silico evaluation of pharmacological properties. Thus, this work aims to develop a computational model (in silico) to predict the intrinsic permeability (Po) of compounds using artificial neural networks (ANNs), built with observations made in 273 molecules, using only in silico calculated descriptors. The second chapter describes the traineeship in Community Pharmacy. This traineeship was conducted in Pharmacy São Cosme, in Covilhã, between February 4th and May 3 r d, 2013. Under the guidance of Dr. Carlos Tavares and the whole team present in the pharmacy, I was given the opportunity to join a team and experience all activities carried out by the pharmacist in this professional field. This report aims to describe the working of a Community Pharmacy, as well as the tasks and responsibilities of the Pharmacist in it. Finally, the third chapter describes the traineeship in Hospital Pharmacy, conducted in the Pharmaceutical Services of Centro Hospitalar Cova da Beira, between May 6th and June 21st of 2013. Under the guidance of Prof.ª Olímpia Fonseca and coworkers assigned to the different areas of the Pharmaceutical Services, I was given the opportunity to participate in various tasks and activities developed in this service. This report aims to describe the activities performed as well as the technical skills acquired

Identification and tracking of maritime objects for collision risk estimation

With the advent of modem high-speed passenger ferries and the general increase in maritime traffic, both commercial and recreational, marine safety is becoming an increasingly important issue. From lightweight catamarans and fishing trawlers to container ships and cruise liners one question remains the same. Is anything in the way? This question is addressed in this thesis. Through the use of image processing techniques applied to video sequences of maritime scenes the images are segmented into two regions, sea and object. This is achieved using statistical measures taken from the histogram data of the images. Each segmented object has a feature vector built containing information including its size and previous centroid positions. The feature vectors are used to track the identified objects across many frames. With information recorded about an object's previous motion its future motion is predicted using a least squares method. Finally a high-level rule-based algorithm is applied in order to estimate the collision risk posed by each object present in the image. The result is an image with the objects identified by the placing of a white box around them. The predicted motion is shown and the estimated collision risk posed by that object is displayed. The algorithms developed in this work have been evaluated using two previously unseen maritime image sequences. These show that the algorithms developed here can be used to estimate the collision risk posed by maritime objects.EThOS - Electronic Theses Online ServiceGBUnited Kingdo