0000000000523166
AUTHOR
Sébastien Roux
At what age did you learn ‘Dog’, ‘Harp’ and other words that you know? The issue of what adult age of acquisition (AoA) estimates really measure
International audience
Comment l’information circule d’un niveau de traitement à l’autre lors de l’accès lexical en production verbale de mots ? Éléments de synthèse
Resume Cet article propose une synthese des principaux travaux sur la question de la transmission de l’activation en production verbale a l’oral. Apres avoir rappele brievement quels sont les differents niveaux des traitement identifies par les chercheurs, nous decrivons trois types d’architectures fonctionnelles – discrete-serielle, en cascade et interactive – qui ont ete proposees pour rendre compte de la maniere dont l’activation se transmet entre les differents niveaux de traitement. Nous exposons ensuite les arguments en faveur de la conception discrete et serielle soutenue par Levelt, Roelofs et Meyer (1999), tout en les critiquant notamment parce qu’ils reposent le plus souvent sur d…
Fast and Robust Face Detection on a Parallel Optimized Architecture implemented on FPGA
In this paper, we present a parallel architecture for fast and robust face detection implemented on FPGA hardware. We propose the first implementation that meets both real-time requirements in an embedded context and face detection robustness within complex backgrounds. The chosen face detection method is the Convolutional Face Finder (CFF) algorithm, which consists of a pipeline of convolution and subsampling operations, followed by a multilayer perceptron. We present the design methodology of our face detection processor element (PE). This methodology was followed in order to optimize our implementation in terms of memory usage and parallelization efficiency. We then built a parallel arch…
Design of a Real-time face detection parallel architecture using High-Level Synthesis
Abstract We describe a High-Level Synthesis implementation of a parallel architecture for face detection. The chosen face detection method is the well-known Convolutional Face Finder (CFF) algorithm, which consists of a pipeline of convolution operations. We rely on dataflow modelling of the algorithm and we use a high-level synthesis tool in order to specify the local dataflows of our Processing Element (PE), by describing in C language inter-PE communication, fine scheduling of the successive convolutions, and memory distribution and bandwidth. Using this approach, we explore several implementation alternatives in order to find a compromise between processing speed and area of the PE. We …
“With a little help from my friends”: Orthographic influences in spoken word recognition
Resume Dans la presente etude, une tâche de decision lexicale auditive a ete utilisee avec des mots consistants (dans la direction phonie-graphie) ayant beaucoup, ou au contraire, peu « d’amis » au sein de leur voisinage phonologique. Les mots ayant beaucoup d’amis ont conduit a des temps de decision de lexicalite plus courts que ceux en ayant peu. Ce resultat est en accord avec l’hypothese selon laquelle l’orthographe faconne la perception des mots entendus du fait d’une restructuration des representations phonologiques par les connaissances orthographiques.
A Parallel Face Detection System Implemented on FPGA
In this paper, we introduce a methodology for designing a system for face detection and its implementation on FPGA. The chosen face detection method is the well-known convolutional face finder (CFF) algorithm, which consists in a pipeline of convolutions and subsampling operations. Our goal is to define a parallel architecture able to process efficiently this algorithm. We present a dataflow based architecture algorithm adequation (AAA) methodology implemented using the SynDEx software, in order to find the best compromise between the processing power and functionality requirement of each processor element (PE), and the efficiency of algorithm parallelization. We describe a first implementa…