Branstad Inaugural speech, January 14, 2011

Inaugural speech by Governor Terry Branstad

Ventral and dorsal pathways of speech perception: An intracerebral ERP study.

Recent theory of physiology of language suggests a dual stream dorsal/ventral organization of speech perception. Using intra-cerebral Event-related potentials (ERPs) during pre-surgical assessment of twelve drug-resistant epileptic patients, we aimed to single out electrophysiological patterns during both lexical-semantic and phonological monitoring tasks involving ventral and dorsal regions respectively. Phonological information processing predominantly occurred in the left supra-marginal gyrus (dorsal stream) and lexico-semantic information occurred in anterior/middle temporal and fusiform gyri (ventral stream). Similar latencies were identified in response to phonological and lexico-semantic tasks, suggesting parallel processing. Typical ERP components were strongly left lateralized since no evoked responses were recorded in homologous right structures. Finally, ERP patterns suggested the inferior frontal gyrus as the likely final common pathway of both dorsal and ventral streams. These results brought out detailed evidence of the spatial-temporal information processing in the dual pathways involved in speech perception.

O vídeo didático "Conhecendo o Solo" e a contribuição desse recurso audiovisual no processo de aprendizagem no ensino fundamental

O uso de recursos audiovisuais no ensino de solos, como estímulo para os alunos, pode auxiliar na construção de um conhecimento crítico e reflexivo. Este trabalho objetivou analisar a contribuição do vídeo "Conhecendo o Solo" no ensino e na aprendizagem dessa temática no nível fundamental. Com o intuito de estimular os alunos a perceber a importância dos solos nos ambientes, esse vídeo foi aplicado como conteúdo de ensino. Em seguida, foi aplicado um questionário, em que os alunos descreveram as principais ideias transmitidas por esse, especificando os pontos positivos e negativos do recurso utilizado. A análise do questionário revelou que o uso do vídeo foi um facilitador da aprendizagem. Porém, as respostas dos estudantes indicaram que alguns aspectos necessitam de adequações, como o dinamismo, a interatividade, a quantidade de informações e a narração. Mesmo assim, o recurso foi classificado pela maioria dos alunos como adequado, e o repertório de conteúdos apresentou similaridade com o exposto no vídeo, caracterizando-o como um recurso de influência positiva no processo de ensino e aprendizagem.

Desafios e avanços na recuperação automática da informação audiovisual

Exposição sobre processos e métodos utilizados para a indexação e recuperação textual da informação semântica em vídeo, tendo como base a identificação e classificação do seu conteúdo visual e sonoro.

La llengua que som(s) : Estudi dialectal audiovisual de la comarca de la Garrotxa

Estudi dialectal audiovisual del parlar de la comarca de la Garrotxa. Seguint el mètode geogràfic emprat pel lingüista mallorquí Joan Veny, hem elaborat vuit enquestes a diversos informants de la zona. L'objectiu és definir sincrònicament els trets lingüístics -fonètics, morfosintàctics i lèxics- del parlar dels garrotxins de més edat i, alhora, posar l'èmfasi en les particularitats lingüístiques de la zona respecte a la resta del català del bloc oriental.

L'audiovisual com a metodologia d'aprenentatge

Aquest projecte està fonamentat teòricament al voltant de dos pilars: l'aprenentatge i l'audiovisual. En primer lloc faré una breu conceptualització de l'aprenentatge que s'ha fet servir per dissenyar el recurs audiovisual d'aquesta pràctica. I, en segon lloc, parlaré de l'audiovisual com a potencial eina educativa.

Non-Linear and Non-Conventional Speech Processing: Alternative Techniques

This special issue aims to cover some problems related to non-linear and nonconventional speech processing. The origin of this volume is in the ISCA Tutorial and Research Workshop on Non-Linear Speech Processing, NOLISP’09, held at the Universitat de Vic (Catalonia, Spain) on June 25–27, 2009. The series of NOLISP workshops started in 2003 has become a biannual event whose aim is to discuss alternative techniques for speech processing that, in a sense, do not fit into mainstream approaches. A selected choice of papers based on the presentations delivered at NOLISP’09 has given rise to this issue of Cognitive Computation.

On the Selection of Non-Invasive Methods Based on Speech Analysis Oriented to Automatic Alzheimer Disease Diagnosis

The work presented here is part of a larger study to identify novel technologies and biomarkers for early Alzheimer disease (AD) detection and it focuses on evaluating the suitability of a new approach for early AD diagnosis by non-invasive methods. The purpose is to examine in a pilot study the potential of applying intelligent algorithms to speech features obtained from suspected patients in order to contribute to the improvement of diagnosis of AD and its degree of severity. In this sense, Artificial Neural Networks (ANN) have been used for the automatic classification of the two classes (AD and control subjects). Two human issues have been analyzed for feature selection: Spontaneous Speech and Emotional Response. Not only linear features but also non-linear ones, such as Fractal Dimension, have been explored. The approach is non invasive, low cost and without any side effects. Obtained experimental results were very satisfactory and promising for early diagnosis and classification of AD patients.

On Automatic Diagnosis of Alzheimer's Disease based on Spontaneous Speech Analysis and Emotional Temperature

Alzheimer's disease is the most prevalent form of progressive degenerative dementia; it has a high socio-economic impact in Western countries. Therefore it is one of the most active research areas today. Alzheimer's is sometimes diagnosed by excluding other dementias, and definitive confirmation is only obtained through a post-mortem study of the brain tissue of the patient. The work presented here is part of a larger study that aims to identify novel technologies and biomarkers for early Alzheimer's disease detection, and it focuses on evaluating the suitability of a new approach for early diagnosis of Alzheimer’s disease by non-invasive methods. The purpose is to examine, in a pilot study, the potential of applying Machine Learning algorithms to speech features obtained from suspected Alzheimer sufferers in order help diagnose this disease and determine its degree of severity. Two human capabilities relevant in communication have been analyzed for feature selection: Spontaneous Speech and Emotional Response. The experimental results obtained were very satisfactory and promising for the early diagnosis and classification of Alzheimer’s disease patients.