173 resultados para speech enhancement


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Abstract Ag-TiO2 and Au-TiO2 hybrid electrodes were designed by covalent attachment of TiO2 nanoparticles to Ag or Au electrodes via an organic linker. The optical and electronic properties of these systems were investigated using the cytochrome b5 (Cyt b5) domain of sulfite oxidase, exclusively attached to the TiO2 surface, as a Raman marker and model redox enzyme. Very strong SERR signals of Cyt b 5 were obtained for Ag-supported systems due to plasmonic field enhancement of Ag. Time-resolved surface-enhanced resonance Raman spectroscopic measurements yielded a remarkably fast electron transfer kinetic (k = 60 s -1) of Cyt b5 to Ag. A much lower Raman intensity was observed for Au-supported systems with undefined and slow redox behavior. We explain this phenomenon on the basis of the different potential of zero charge of the two metals that largely influence the electronic properties of the TiO2 island film. © 2013 American Chemical Society.

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This paper demonstrates a renewed procedure for the quantification of surface-enhanced Raman scattering (SERS) enhancement factors with improved precision. The principle of this method relies on deducting the resonance Raman scattering (RRS) contribution from surface-enhanced resonance Raman scattering (SERRS) to end up with the surface enhancement (SERS) effect alone. We employed 1,8,15,22-tetraaminophthalocyanato-cobalt(II) (4α-CoIITAPc), a resonance Raman- and electrochemically redox-active chromophore, as a probe molecule for RRS and SERRS experiments. The number of 4α-CoIITAPc molecules contributing to RRS and SERRS phenomena on plasmon inactive glassy carbon (GC) and plasmon active GC/Au surfaces, respectively, has been precisely estimated by cyclic voltammetry experiments. Furthermore, the SERS substrate enhancement factor (SSEF) quantified by our approach is compared with the traditionally employed methods. We also demonstrate that the present approach of SSEF quantification can be applied for any kind of different SERS substrates by choosing an appropriate laser line and probe molecule.

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This communication presents a new pathway for the more precise quantification of surface-enhanced Raman scattering (SERS) enhancement factor via deducing resonance Raman scattering (RRS) effect from surface-enhanced resonance Raman scattering (SERRS). To achieve this, a self-assembled monolayer of 1,8,15,22-tetraaminophthalocyanatocobalt(II) (4α-CoIITAPc) is formed on plasmon inactive glassy carbon (GC) and plasmon active GC/AuNPs surface. The surfaces are subsequently used as common probes for electrochemical and Raman (RRS and SERRS) studies. The most crucial parameters required for the quantification of SERS substrate enhancement factor (SSEF) such as real surface area of GC/AuNPs substarte and the number of 4α-CoIITAPc molecules contributing to RRS (on GC) and SERRS (on GC/AuNPs) are precisely estimated by cyclic voltammetry experiments. The present approach of SSEF quantification can be applied to varieties of surfaces by choosing an appropriate laser line and probe molecule for each surface.

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Spanning over a considerable length of time, facility management is a key phase in the development cycle of built assets. Therefore facility managers are in a commanding position to maximise the potential of sustainability through the operation, maintenance and upgrade of built facilities leading to decommission and deconstruction. Sustainability endeavours in facility management practices will not only contribute to reducing energy consumption, waste and running costs, but also help improve organisational productivity, financial returns and community standing of the organisation. At the forefront facing sustainability challenge, facility manager should be empowered with the necessary knowledge and capabilities. However, literature studies show a gap between the current level of awareness and the specific knowledge and necessary skills required to pursue sustainability in the profession. People capability is considered as the key enabler in managing the sustainability agenda as well as being central to the improvement of competency and innovation in an organization. This paper aims to identify the critical factors for enhancing people capabilities in promoting the sustainability agenda in facility management practices. Starting with a total of 60 factors identified through literature review, the authors conducted a questionnaire survey to assess the perceived importance of these factors. The findings reveal 23 critical factors as significantly important. They form the basis of a mechanism framework developed to equip facility managers with the right knowledge, to continue education and training and to develop new mind-sets to enhance the implementation of sustainability measures in FM practices.

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Texture enhancement is an important component of image processing that finds extensive application in science and engineering. The quality of medical images, quantified using the imaging texture, plays a significant role in the routine diagnosis performed by medical practitioners. Most image texture enhancement is performed using classical integral order differential mask operators. Recently, first order fractional differential operators were used to enhance images. Experimentation with these methods led to the conclusion that fractional differential operators not only maintain the low frequency contour features in the smooth areas of the image, but they also nonlinearly enhance edges and textures corresponding to high frequency image components. However, whilst these methods perform well in particular cases, they are not routinely useful across all applications. To this end, we apply the second order Riesz fractional differential operator to improve upon existing approaches of texture enhancement. Compared with the classical integral order differential mask operators and other first order fractional differential operators, we find that our new algorithms provide higher signal to noise values and superior image quality.

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Vision-based underwater navigation and obstacle avoidance demands robust computer vision algorithms, particularly for operation in turbid water with reduced visibility. This paper describes a novel method for the simultaneous underwater image quality assessment, visibility enhancement and disparity computation to increase stereo range resolution under dynamic, natural lighting and turbid conditions. The technique estimates the visibility properties from a sparse 3D map of the original degraded image using a physical underwater light attenuation model. Firstly, an iterated distance-adaptive image contrast enhancement enables a dense disparity computation and visibility estimation. Secondly, using a light attenuation model for ocean water, a color corrected stereo underwater image is obtained along with a visibility distance estimate. Experimental results in shallow, naturally lit, high-turbidity coastal environments show the proposed technique improves range estimation over the original images as well as image quality and color for habitat classification. Furthermore, the recursiveness and robustness of the technique allows implementation onboard an Autonomous Underwater Vehicle for improving navigation and obstacle avoidance performance.

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Modern power systems have become more complex due to the growth in load demand, the installation of Flexible AC Transmission Systems (FACTS) devices and the integration of new HVDC links into existing AC grids. On the other hand, the introduction of the deregulated and unbundled power market operational mechanism, together with present changes in generation sources including connections of large renewable energy generation with intermittent feature in nature, have further increased the complexity and uncertainty for power system operation and control. System operators and engineers have to confront a series of technical challenges from the operation of currently interconnected power systems. Among the many challenges, how to evaluate the steady state and dynamic behaviors of existing interconnected power systems effectively and accurately using more powerful computational analysis models and approaches becomes one of the key issues in power engineering. The traditional computing techniques have been widely used in various fields for power system analysis with varying degrees of success. The rapid development of computational intelligence, such as neural networks, fuzzy systems and evolutionary computation, provides tools and opportunities to solve the complex technical problems in power system planning, operation and control.

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This paper reports on the experimental testing of oxygen-enriched porous fuel injection in a scramjet engine. Fuel was injected via inlet mounted, oxide-based ceramic matrix composite (CMC) injectors on both flow path surfaces that covered a total of 9.2 % of the intake surface area. All experiments were performed at an enthalpy of 3.93−4.25±3.2% MJ kg−1, flight Mach number 9.2–9.6 and an equivalence ratio of 0.493±3%. At this condition, the engine was shown to be on the verge of achieving appreciable combustion. Oxygen was then added to the fuel prior to injection such that two distinct enrichment levels were achieved. Combustion was found to increase, by as much as 40 % in terms of combustion-induced pressure rise, over the fuel-only case with increasing oxygen enrichment. Further, the onset of combustion was found to move upstream with increasing levels of oxygen enrichment. Thrust, both uninstalled and specific, and specific impulse were found to be improved with oxygen enrichment. Enhanced fuel–air mixing due to the pre-mixing of oxygen with the fuel together with the porous fuel injection are believed to be the main contributors to the observed enhanced performance of the tested engine.

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A silk protein, fibroin, was isolated from the cocoons of the domesticated silkworm (Bombyx mori) and cast into membranes to serve as freestanding templates for tissue-engineered corneal cell constructs to be used in ocular surface reconstruction. In this study, we sought to enhance the attachment and proliferation of corneal epithelial cells by increasing the permeability of the fibroin membranes and the topographic roughness of their surface. By mixing the fibroin solution with poly(ethylene glycol) (PEG) of molecular weight 300 Da, membranes were produced with increased permeability and with topographic patterns generated on their surface. In order to enhance their mechanical stability, some PEG-treated membranes were also crosslinked with genipin. The resulting membranes were thoroughly characterized and compared to the non-treated membranes. The PEG-treated membranes were similar in tensile strength to the non-treated ones, but their elastic modulus was higher and elongation lower, indicating enhanced rigidity. The crosslinking with genipin did not induce a significant improvement in mechanical properties. In cultures of a human-derived corneal epithelial cell line (HCE-T), the PEG treatment of the substratum did not improve the attachment of cells and it enhanced only slightly the cell proliferation in the longer term. Likewise, primary cultures of human limbal epithelial cells grew equally well on both non-treated and PEG-treated membranes, and the stratification of cultures was consistently improved in the presence of an underlying culture of irradiated 3T3 feeder cells, irrespectively of PEG-treatment. Nevertheless, the cultures grown on the PEG-treated membranes in the presence of feeder cells did display a higher nuclear-to-cytoplasmic ratio suggesting a more proliferative phenotype. We concluded that while the treatment with PEG had a significant effect on some structural properties of the B. mori silk fibroin (BMSF) membranes, there were minimal gains in the performance of these materials as a substratum for corneal epithelial cell growth. The reduced mechanical stability of freestanding PEG-treated membranes makes them a less viable choice than the non-treated membranes.

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The significant physical, emotional, educational and social developmental challenges faced by adolescents and young adults are associated with high levels of emotional vulnerability. Thus, the development and use of effective emotion-regulation strategies during this period is critical. Music listening is commonly used by young people to identify, express, enhance and regulate their emotions. Modern mobile technology provides an engaging, easily accessible means of assisting young people with identifying and managing emotions through music. A systematic contextual review of iPhone applications addressing emotions through music was conducted. Their quality was evaluated by two independent raters using the Mobile App Rating Scale (MARS). Three participatory design workshops (PDW; N=13, 6 males, 7 females; age 15-25) were conducted, exploring young people’s use of music to enhance wellbeing. Young people were also asked to trial existing mood and music apps and to conceptualise their ultimate mood-targeting music application. Of the identified 117 music apps, 20 met inclusion criteria (to play songs, not sounds; priced below $5.00). Characteristics and overall quality of the music apps are described and key features of the five highest- rating apps are presented. Thematic analysis of the PDW content identified the following music affect- regulation strategies: relationship building, modifying cognitions, modifying emotions, and immersing in emotions (i.e. habituation or mood enhancement). The application of key learnings from the mobile app review and PDW to the design and development of the new music eScape app will be presented. Implications for future research and for applying the new app in clinical practice are discussed.

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We propose a novel technique for conducting robust voice activity detection (VAD) in high-noise recordings. We use Gaussian mixture modeling (GMM) to train two generic models; speech and non-speech. We then score smaller segments of a given (unseen) recording against each of these GMMs to obtain two respective likelihood scores for each segment. These scores are used to compute a dissimilarity measure between pairs of segments and to carry out complete-linkage clustering of the segments into speech and non-speech clusters. We compare the accuracy of our method against state-of-the-art and standardised VAD techniques to demonstrate an absolute improvement of 15% in half-total error rate (HTER) over the best performing baseline system and across the QUT-NOISE-TIMIT database. We then apply our approach to the Audio-Visual Database of American English (AVDBAE) to demonstrate the performance of our algorithm in using visual, audio-visual or a proposed fusion of these features.

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For most people, speech production is relatively effortless and error-free. Yet it has long been recognized that we need some type of control over what we are currently saying and what we plan to say. Precisely how we monitor our internal and external speech has been a topic of research interest for several decades. The predominant approach in psycholinguistics has assumed monitoring of both is accomplished via systems responsible for comprehending others' speech. This special topic aimed to broaden the field, firstly by examining proposals that speech production might also engage more general systems, such as those involved in action monitoring. A second aim was to examine proposals for a production-specific, internal monitor. Both aims require that we also specify the nature of the representations subject to monitoring.

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This large-scale longitudinal population study provided a rare opportunity to consider the interface between multilingualism and speech-language competence on children’s academic and social-emotional outcomes and to determine whether differences between groups at 4 to 5 years persist, deepen, or disappear with time and schooling. Four distinct groups were identified from the Kindergarten cohort of the Longitudinal Study of Australian Children (LSAC) (1) English-only + typical speech and language (n = 2,012); (2) multilingual + typical speech and language (n = 476); (3) English-only + speech and language concern (n = 643); and (4) multilingual + speech and language concern (n = 109). Two analytic approaches were used to compare these groups. First, a matched case-control design was used to randomly match multilingual children with speech and language concern (group 4, n = 109) to children in groups 1, 2, and 3 on gender, age, and family socio-economic position in a cross-sectional comparison of vocabulary, school readiness, and behavioral adjustment. Next, analyses were applied to the whole sample to determine longitudinal effects of group membership on teachers’ ratings of literacy, numeracy, and behavioral adjustment at ages 6 to 7 and 8 to 9 years. At 4 to 5 years, multilingual children with speech and language concern did equally well or better than English-only children (with or without speech and language concern) on school readiness tests but performed more poorly on measures of English vocabulary and behavior. At ages 6 to 7 and 8 to 9, the early gap between English-only and multilingual children had closed. Multilingualism was not found to contribute to differences in literacy and numeracy outcomes at school; instead, outcomes were more related to concerns about children’s speech and language in early childhood. There were no group differences for socio-emotional outcomes. Early evidence for the combined risks of multilingualism plus speech and language concern was not upheld into the school years.

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An innovative design strategy for light emitting field effect transistors (LEFETs) to harvest higher luminance and switching is presented. The strategy uses a non-planar electrode geometry in tri-layer LEFETs for simultaneous enhancement of the key parameters of quantum efficiency, brightness, switching, and mobility across the RGB color gamut.