Robust Automatic Speech recognition System Implemented in a Hybrid Design DSP-FPGA

The aim of this work is to reduce the burden task on the DSP processor by transferring a parallel computation part on a configurable circuits FPGA, in automatic speech recognition module design, signal pre-processing, feature selection and optimization, models construction and finally classification phase are necessary. LMS filter algorithm that contains more parallelism and more MACs (multiply and Accumulate) operations is implemented on FPGA Virtex 5 by Xilings, MFCCs features extraction and DTW ( dynamic time wrapping) method is used as a classifier. Major contribution of this work are hybrid solution DSP and FPGA in real time speech recognition system design, the optimization of number of MAC-core within the FPGA this result is obtained by sharing MAC resources between two operation phases: computation of output filter and updating LMS filter coefficients. The paper also provides a hardware solution of the filter with detailed description of asynchronous interface of FPGA circuit and TMS320C6713-EMIF component. The results of simulation shows an improvement in time computation and by optimizing the implementation on the FPGA a gain in space consumption is obtained

Station hybride (DSP/FPGA) pour un système rapide de reconnaissance automatique de la parole: Hybrid station (DSP/FPGA) for fast automatic speech recognition system

La reconnaissance automatique de la parole (RAP) a fait l’objet de plusieurs investigations depuis le début des années 50. La nature complexe de la parole oblige, l’auditeur humain à utiliser plusieurs niveaux de traitement pour ce domaine. Le 1er niveau est la détermination des caractéristiques du signal de la parole lui-même, c'est-à-dire l’analyse acoustique. Les niveaux phonétique, lexical et sémantique, etc. c’est dire combien chez l’être humain la reconnaissance et la compréhension de la parole sont fortement liées. Le but du présent travail est la réalisation d’un système embarqué (DSP/FPGA) pour le domaine de RAP fonctionnant en temps réel. Pour atteindre ce but, nous avons matérialisé quelques parties du système RAP implémenté sur DSP comme le filtre LMS et le coeur de la distance DTW (accélérateurs matériels) sur FPGA. Cette implantation nous permet d’accélérer le processus de la reconnaissance donc une augmentation considérable du dictionnaire de références. The automatic speech recognition (ASR) has been the subject of several research studies since the early 50s. And because of the complex nature of speech, human listener uses several levels of treatment for this domain. The first level is the determination of the speech signal characteristics itself, i.e the acoustic analysis. Then comes the phonetics, lexical and semantic levels,etc. This shows how human’s recognition and speech understanding are strongly related. The purpose of this work is to design an embedded ASR system based on (DSP/FPGA) functioning/operating in real time. To achieve this goal, we have materialized and implemented some parts of the ASR system on DSP and other parts such as the LMS filter and the core of the DTW distance (hardware accelerators) on FPGA, this hybrid implementation allows us to accelerate the process of automatic speech recognition, so it can be used on real time applications to help us reach a considerable increase amount of words in the reference dictionary

Dinoflagellates encystment with emphasis on blooms in Boughrara Lagoon (South-Western Mediterranean): Combined effects of trace metal concentration and environmental context

International audienc

Effects of physical forcing on COastal ZOoplankton community structure: study of the unusual case of a MEDiterranean ecosystem under strong tidal influence (Project COZOMED-MERMEX).

International audienceThe COZOMED-MERMEX project aims at understanding how hydrodynamic forcing (currents, tides, winds)combine with anthropogenic forcing and climate to affect the variability of coastal Mediterranean zooplanktoncommunities under contrasting tidal influence. This study includes (i) a zero state of knowledge via a literaturereview of existing data and (ii) a case study on the system Boughrara lagoon - Gulf of Gabes. This ecosystemgives major services for Tunisia (about 65% of national fish production) but is weakened by its situation in aheavily anthropized area and under influence of urban, industrial and agricultural inputs. Besides this regionis subject to specific climate forcing (Sahelian winds, scorching heat, intense evaporation, flooding) whichpossible changes will be considered. The expected issues are (i) to improve our knowledge of hydrodynamicforcing on zooplankton and ultimately on the functioning of coastal Mediterranean ecosystems impacted byanthropogenic and climatic effects and (ii) to elaborate management tools to help preserving good ecologicalstatus of these ecosystems: hydrodynamic circulation model, mapping of isochrones of residence times, mappingof the areas of highest zooplankton abundances (swarms), and sensitive areas, etc. This project strengthensexisting scientific collaborations within the MERMEX program (The MerMex Group, 2011) and in the frameof an international joint laboratory (COSYS-Med) created in 2014. A first field mulidisciplinary campaign wasperformed in October 2016. The strategy combined measurements of sea level and currents (mooring of ADCP,Argonaute and tidal gauges), hydrological description of water masses (horizontal and vertical transect with aMinibat equipped with CTD, fluorescence and turbidity sensors) and discrete sampling of nutrients, DOC, POC,pico, nano, microphytoplankton and mesozooplankton. The first results allow a description of water currents andshows a good coupling between tidal cycles (ebb-flood and spring tide neap tide) and the dynamics of planktoniccompartments in the lagoon