905 resultados para audio-visual content distribution


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El v??deo est?? realizado por profesores de las ??reas de Did??ctica y Organizaci??n Escolar y Teor??a e Historia de la Educaci??n, durante los a??os 2000 y 2001. Recoge la opini??n de profesionales, padres y madres y personas con discapacidad f??sica (sordos, ciegos y P.C.I.)y personas con discapacidad mental en relaci??n con diferentes aspectos de la vida diaria: hogar, inserci??n laboral, etc. Este recurso did??ctico est?? dise??ado para el visionado, interpretaci??n te??rico-pr??ctica y contraste de opiniones en el aula, de ense??anza superior, para abordar la formaci??n de los profesionales que van a desarrollar su actividad con personas con discapacidad.

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La función de la Lengua en el Bachillerato es triple: como factor de promoción socio-económica que permite en algunos casos obtener mejoras salariales y en otros alcanzar puestos vedados a los que no conocen idiomas, la UNESCO recomienda su estudio por su función educativa respecto al ser humano, integrante de los distintos grupos nacionales, enriquecimiento del sentido crítico y de tolerancia al apreciar las diferencias y semejanzas de los distintos pueblos, una cultura humanista que debe procurar el estudio de la lengua francesa, máxime para nosotros si tenemos en cuenta que es un país fronterizo nuestro y que permite el camino para llegar a Europa, es lógico que la lengua francesa sea tan importante para nosotros debido a las relaciones comerciales, económicas, etcétera que se desarrollan en esta lengua.; como tercera función, y primordial, el apredizaje de, por lo menos, un idioma, es primordial para la formación de la personalidad. A partir de 1975 son importantes los avances conseguidos en el estudio de un idioma, sobre todo los esfuerzos de renovación didáctica, destacando las aportaciones de la metodología estructuroglobal audiovisual, nacida a partir de los años cincuenta y que está siendo renovada constantemente. Si el alumno ha de aprender el francés a distancia debe tener un material adecuado a través de cassettes con diálogos para aprender a pronunciar correctamente. Después se aprenderá a leer y escribir porque se supone que se sabe pronunciar correctamente y el transcribir la lengua oral es un ejercicio para fijar los conocimientos. Pero el aprendizaje de un idioma debe realizarse dedicando todos los días un tiempo concreto, esta regularidad es la permite aprenderlo. Así, en cada caso el alumno deberá actuar de acuerdo con las orientaciones más precisas y personales de su profesor-tutor y con sus hábitos de trabajo siempre y cuando resulten eficaces.

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This dissertation examines auditory perception and audio-visual reception in noise for both hearing-impaired and normal hearing persons, with a goal of determining some of the noise conditions under which amplified acoustic cues for speech can be beneficial to hearing-impaired persons.

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In this paper, we introduce a novel high-level visual content descriptor which is devised for performing semantic-based image classification and retrieval. The work can be treated as an attempt to bridge the so called “semantic gap”. The proposed image feature vector model is fundamentally underpinned by the image labelling framework, called Collaterally Confirmed Labelling (CCL), which incorporates the collateral knowledge extracted from the collateral texts of the images with the state-of-the-art low-level image processing and visual feature extraction techniques for automatically assigning linguistic keywords to image regions. Two different high-level image feature vector models are developed based on the CCL labelling of results for the purposes of image data clustering and retrieval respectively. A subset of the Corel image collection has been used for evaluating our proposed method. The experimental results to-date already indicates that our proposed semantic-based visual content descriptors outperform both traditional visual and textual image feature models.

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There are still major challenges in the area of automatic indexing and retrieval of multimedia content data for very large multimedia content corpora. Current indexing and retrieval applications still use keywords to index multimedia content and those keywords usually do not provide any knowledge about the semantic content of the data. With the increasing amount of multimedia content, it is inefficient to continue with this approach. In this paper, we describe the project DREAM, which addresses such challenges by proposing a new framework for semi-automatic annotation and retrieval of multimedia based on the semantic content. The framework uses the Topic Map Technology, as a tool to model the knowledge automatically extracted from the multimedia content using an Automatic Labelling Engine. We describe how we acquire knowledge from the content and represent this knowledge using the support of NLP to automatically generate Topic Maps. The framework is described in the context of film post-production.

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There are still major challenges in the area of automatic indexing and retrieval of digital data. The main problem arises from the ever increasing mass of digital media and the lack of efficient methods for indexing and retrieval of such data based on the semantic content rather than keywords. To enable intelligent web interactions or even web filtering, we need to be capable of interpreting the information base in an intelligent manner. Research has been ongoing for a few years in the field of ontological engineering with the aim of using ontologies to add knowledge to information. In this paper we describe the architecture of a system designed to automatically and intelligently index huge repositories of special effects video clips, based on their semantic content, using a network of scalable ontologies to enable intelligent retrieval.

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In this paper, we introduce a novel high-level visual content descriptor devised for performing semantic-based image classification and retrieval. The work can be treated as an attempt for bridging the so called "semantic gap". The proposed image feature vector model is fundamentally underpinned by an automatic image labelling framework, called Collaterally Cued Labelling (CCL), which incorporates the collateral knowledge extracted from the collateral texts accompanying the images with the state-of-the-art low-level visual feature extraction techniques for automatically assigning textual keywords to image regions. A subset of the Corel image collection was used for evaluating the proposed method. The experimental results indicate that our semantic-level visual content descriptors outperform both conventional visual and textual image feature models.

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The encoding of goal-oriented motion events varies across different languages. Speakers of languages without grammatical aspect (e.g., Swedish) tend to mention motion endpoints when describing events, e.g., “two nuns walk to a house,”, and attach importance to event endpoints when matching scenes from memory. Speakers of aspect languages (e.g., English), on the other hand, are more prone to direct attention to the ongoingness of motion events, which is reflected both in their event descriptions, e.g., “two nuns are walking.”, and in their non-verbal similarity judgements. This study examines to what extent native speakers of Swedish (n = 82) with English as a foreign language (FL) restructure their categorisation of goal-oriented motion as a function of their English proficiency and experience with the English language (e.g., exposure, learning). Seventeen monolingual native English speakers from the United Kingdom (UK) were engaged for comparison purposes. Data on motion event cognition were collected through a memory-based triads matching task, in which a target scene with an intermediate degree of endpoint orientation was matched with two alternative scenes with low and high degrees of endpoint orientation, respectively. Results showed that the preference among the Swedish speakers of L2 English to base their similarity judgements on ongoingness rather than event endpoints was correlated with their use of English in their everyday lives, such that those who often watched television in English approximated the ongoingness preference of the English native speakers. These findings suggest that event cognition patterns may be restructured through the exposure to FL audio-visual media. The results thus add to the emerging picture that learning a new language entails learning new ways of observing and reasoning about reality.

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Synesthesia entails a special kind of sensory perception, where stimulation in one sensory modality leads to an internally generated perceptual experience of another, not stimulated sensory modality. This phenomenon can be viewed as an abnormal multisensory integration process as here the synesthetic percept is aberrantly fused with the stimulated modality. Indeed, recent synesthesia research has focused on multimodal processing even outside of the specific synesthesia-inducing context and has revealed changed multimodal integration, thus suggesting perceptual alterations at a global level. Here, we focused on audio-visual processing in synesthesia using a semantic classification task in combination with visually or auditory-visually presented animated and in animated objects in an audio-visual congruent and incongruent manner. Fourteen subjects with auditory-visual and/or grapheme-color synesthesia and 14 control subjects participated in the experiment. During presentation of the stimuli, event-related potentials were recorded from 32 electrodes. The analysis of reaction times and error rates revealed no group differences with best performance for audio-visually congruent stimulation indicating the well-known multimodal facilitation effect. We found enhanced amplitude of the N1 component over occipital electrode sites for synesthetes compared to controls. The differences occurred irrespective of the experimental condition and therefore suggest a global influence on early sensory processing in synesthetes.

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Contiene informacion sobre el Proyecto III del programa de trabajo del CCCT: preparacion e intercambio de material audiovisual para la educacion sobre los beneficios, limitaciones y peligros del desarrollo en ciencia y tecnologia.

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Primate multisensory object perception involves distributed brain regions. To investigate the network character of these regions of the human brain, we applied data-driven group spatial independent component analysis (ICA) to a functional magnetic resonance imaging (fMRI) data set acquired during a passive audio-visual (AV) experiment with common object stimuli. We labeled three group-level independent component (IC) maps as auditory (A), visual (V), and AV, based on their spatial layouts and activation time courses. The overlap between these IC maps served as definition of a distributed network of multisensory candidate regions including superior temporal, ventral occipito-temporal, posterior parietal and prefrontal regions. During an independent second fMRI experiment, we explicitly tested their involvement in AV integration. Activations in nine out of these twelve regions met the max-criterion (A < AV > V) for multisensory integration. Comparison of this approach with a general linear model-based region-of-interest definition revealed its complementary value for multisensory neuroimaging. In conclusion, we estimated functional networks of uni- and multisensory functional connectivity from one dataset and validated their functional roles in an independent dataset. These findings demonstrate the particular value of ICA for multisensory neuroimaging research and using independent datasets to test hypotheses generated from a data-driven analysis.

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Audio-visual documents obtained from German TV news are classified according to the IPTC topic categorization scheme. To this end usual text classification techniques are adapted to speech, video, and non-speech audio. For each of the three modalities word analogues are generated: sequences of syllables for speech, “video words” based on low level color features (color moments, color correlogram and color wavelet), and “audio words” based on low-level spectral features (spectral envelope and spectral flatness) for non-speech audio. Such audio and video words provide a means to represent the different modalities in a uniform way. The frequencies of the word analogues represent audio-visual documents: the standard bag-of-words approach. Support vector machines are used for supervised classification in a 1 vs. n setting. Classification based on speech outperforms all other single modalities. Combining speech with non-speech audio improves classification. Classification is further improved by supplementing speech and non-speech audio with video words. Optimal F-scores range between 62% and 94% corresponding to 50% - 84% above chance. The optimal combination of modalities depends on the category to be recognized. The construction of audio and video words from low-level features provide a good basis for the integration of speech, non-speech audio and video.