369 resultados para Medical Speech
Resumo:
This study proposes a new product development (NPD) model that aims to improve the effectiveness of innovative NPD in the medical devices. By adopting open innovation theory and applying an in-depth investigation methodology, this paper proposes a knowledge cluster that improves the integration of interdisciplinary human resources and enhances the acquirement of innovative technologies. A knowledge cluster approach helps gather, organise, synthesise, and accumulate knowledge in order to become the impetus for innovation. Although enterprises are no longer the principals of research and development, they should still be capable of integrating professional physicians, external groups, and individuals through the knowledge cluster platform. However, in order to support an effective NPD model, enterprises should provide adequate incentives and trust to external individuals or groups willing to contribute their expertise and knowledge to this knowledge cluster platform. Copyright © 2013 Inderscience Enterprises Ltd.
Resumo:
This paper presents a complete system for expressive visual text-to-speech (VTTS), which is capable of producing expressive output, in the form of a 'talking head', given an input text and a set of continuous expression weights. The face is modeled using an active appearance model (AAM), and several extensions are proposed which make it more applicable to the task of VTTS. The model allows for normalization with respect to both pose and blink state which significantly reduces artifacts in the resulting synthesized sequences. We demonstrate quantitative improvements in terms of reconstruction error over a million frames, as well as in large-scale user studies, comparing the output of different systems. © 2013 IEEE.
Resumo:
Large margin criteria and discriminative models are two effective improvements for HMM-based speech recognition. This paper proposed a large margin trained log linear model with kernels for CSR. To avoid explicitly computing in the high dimensional feature space and to achieve the nonlinear decision boundaries, a kernel based training and decoding framework is proposed in this work. To make the system robust to noise a kernel adaptation scheme is also presented. Previous work in this area is extended in two directions. First, most kernels for CSR focus on measuring the similarity between two observation sequences. The proposed joint kernels defined a similarity between two observation-label sequence pairs on the sentence level. Second, this paper addresses how to efficiently employ kernels in large margin training and decoding with lattices. To the best of our knowledge, this is the first attempt at using large margin kernel-based log linear models for CSR. The model is evaluated on a noise corrupted continuous digit task: AURORA 2.0. © 2013 IEEE.
Resumo:
Biodegradable polymers can be applied to a variety of implants for controlled and local drug delivery. The aim of this study is to develop a biodegradable and nanoporous polymeric platform for a wide spectrum of drug-eluting implants with special focus on stent-coating applications. It was synthesized by poly(DL-lactide-co-glycolide) (PLGA 65:35, PLGA 75:25) and polycaprolactone (PCL) in a multilayer configuration by means of a spin-coating technique. The antiplatelet drug dipyridamole was loaded into the surface nanopores of the platform. Surface characterization was made by atomic force microscopy (AFM) and spectroscopic ellipsometry (SE). Platelet adhesion and drug-release kinetic studies were then carried out. The study revealed that the multilayer films are highly nanoporous, whereas the single layers of PLGA are atomically smooth and spherulites are formed in PCL. Their nanoporosity (pore diameter, depth, density, surface roughness) can be tailored by tuning the growth parameters (eg, spinning speed, polymer concentration), essential for drug-delivery performance. The origin of pore formation may be attributed to the phase separation of polymer blends via the spinodal decomposition mechanism. SE studies revealed the structural characteristics, film thickness, and optical properties even of the single layers in the triple-layer construct, providing substantial information for drug loading and complement AFM findings. Platelet adhesion studies showed that the dipyridamole-loaded coatings inhibit platelet aggregation that is a prerequisite for clotting. Finally, the films exhibited sustained release profiles of dipyridamole over 70 days. These results indicate that the current multilayer phase therapeutic approach constitutes an effective drug-delivery platform for drug-eluting implants and especially for cardiovascular stent applications.
Resumo:
PET/SiO2 layers were chemically modified to maintain immobilization of functional single molecules. GFP molecules provide an ideal system due to their stability and intrinsic fluorescence. GFP in vivo biotinylated within its NH2-terminal region and attached on the substrate via the biotinstreptavidin bond was further investigated with confocal microscopy, atomic force microscopy (AFM) and spectroscopic ellipsometry (SE). AFM revealed monolayered donut-like structures representing assemblies of biotinstreptavidinbiotinGFP immobilized onto PET/SiO2 surfaces via mPEG. In particular, regions with an approximate height of 12 nm, which approaches the molecular dimensions of the above complex given by molecular modeling, could be detected. The dimensions of the donut-like structures suggest a close-to-each-other positioning of the GFP molecules - which, however, retain their functionality, as evidenced by confocal microscopy. © 2011 World Scientific Publishing Company.
Resumo:
This paper presents an overview of the Text-to-Speech synthesis system developed at the Institute for Language and Speech Processing (ILSP). It focuses on the key issues regarding the design of the system components. The system currently fully supports three languages (Greek, English, Bulgarian) and is designed in such a way to be as language and speaker independent as possible. Also, experimental results are presented which show that the system produces high quality synthetic speech in terms of naturalness and intelligibility. The system was recently ranked among the first three systems worldwide in terms of achieved quality for the English language, at the international Blizzard Challenge 2013 workshop. © 2014 Springer International Publishing.