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

Navigation pour robot avec garantie de sécurité basée sur la théorie de la viabilité

Guaranteeing safe, i.e. collision-free, motion for robotic systems is usually tackled in the InevitableCollision State framework. This paper explores the use of the more general Viability theory as analternative when safe motion involves multiple motion constraints and not just collision avoidance. Centralto Viability is the so-called viability kernel, i.e. the set of states of the robotic system for which there isat least one trajectory that satisfies the motion constraints forever. The paper presents an algorithm thatcomputes off-line an approximation of the viability kernel that is both conservative and able to handletime-varying constraints such as moving obstacles. Then it demonstrates, for different robotic scenarios involvingmultiple motion constraints (collision avoidance, visibility, velocity), how to use the viability kernelcomputed off-line within an on-line reactive navigation scheme that can drive the robotic system withoutever violating the motion constraints at hand.La garantie de mouvement sans collision pour les systèmes robotiques est généralement abordéedans le cadre des Etats de Collision Inévitable. Cet article explore l’utilisation de la théorie plusgénérale de la Viabilité comme alternative lorsque le mouvement implique des contraintes de mouvementautres que l’évitement de collision. Le noyau de viabilité, i.e. l’ensemble des états du systèmerobotique pour lequel il existe au moins une trajectoire qui satisfait à jamais les contraintes de mouvement,est un élément central de la théorie de la viabilité. Cet article présente un algorithme qui calculehors ligne une approximation du noyau de viabilité qui est à la fois conservative et capable de gérer descontraintes dynamiques telles que des obstacles mobiles. Ensuite, il démontre, pour différents scénariosrobotiques impliquant plusieurs contraintes de mouvement (évitement de collision, visibilité, vitesse),comment utiliser le noyau de viabilité calculé hors ligne dans un schéma de navigation réactive en lignecapable de piloter le système robotique sans jamais violer les différentes contraintes de mouvement

Viability-Based Guaranteed Safe Robot Navigation

International audienceGuaranteeing safe, i.e. collision-free, motion for robotic systems is usually tackled in the Inevitable Collision State (ICS) framework. This paper explores the use of the more general Viability theory as an alternative when safe motion involves multiple motion constraints and not just collision avoidance. Central to Viability is the so-called viability kernel, i.e. the set of states of the robotic system for which there is at least one trajectory that satisfies the motion constraints forever. The paper presents an algorithm that computes off-line an approximation of the viability kernel that is both conservative and able to handle time-varying constraints such as moving obstacles. Then it demonstrates, for different robotic scenarios involving multiple motion constraints (collision avoidance, visibility, velocity), how to use the viability kernel computed off-line within an on-line reactive navigation scheme that can drive the robotic system without ever violating the motion constraints at hand

Navigation pour robot avec garantie de sécurité basée sur la théorie de la viabilité

Guaranteeing safe, i.e. collision-free, motion for robotic systems is usually tackled in the InevitableCollision State framework. This paper explores the use of the more general Viability theory as analternative when safe motion involves multiple motion constraints and not just collision avoidance. Centralto Viability is the so-called viability kernel, i.e. the set of states of the robotic system for which there isat least one trajectory that satisfies the motion constraints forever. The paper presents an algorithm thatcomputes off-line an approximation of the viability kernel that is both conservative and able to handletime-varying constraints such as moving obstacles. Then it demonstrates, for different robotic scenarios involvingmultiple motion constraints (collision avoidance, visibility, velocity), how to use the viability kernelcomputed off-line within an on-line reactive navigation scheme that can drive the robotic system withoutever violating the motion constraints at hand.La garantie de mouvement sans collision pour les systèmes robotiques est généralement abordéedans le cadre des Etats de Collision Inévitable. Cet article explore l’utilisation de la théorie plusgénérale de la Viabilité comme alternative lorsque le mouvement implique des contraintes de mouvementautres que l’évitement de collision. Le noyau de viabilité, i.e. l’ensemble des états du systèmerobotique pour lequel il existe au moins une trajectoire qui satisfait à jamais les contraintes de mouvement,est un élément central de la théorie de la viabilité. Cet article présente un algorithme qui calculehors ligne une approximation du noyau de viabilité qui est à la fois conservative et capable de gérer descontraintes dynamiques telles que des obstacles mobiles. Ensuite, il démontre, pour différents scénariosrobotiques impliquant plusieurs contraintes de mouvement (évitement de collision, visibilité, vitesse),comment utiliser le noyau de viabilité calculé hors ligne dans un schéma de navigation réactive en lignecapable de piloter le système robotique sans jamais violer les différentes contraintes de mouvement

An Improved GMM-SVM System based on Distance Metric for Voice Pathology Detection

As acoustic signal generated from vocal folds is directly affected by vocal tract pathologies, it can be an effective tool for diagnosis purpose. In this work, we present an efficient method for voice pathology detection based on speech signal processing and machine learning techniques. In the proposed method, we used MFCC to represent the signal features, and we chose to combine GMM and SVMclassifiers to benefit from their generative and discriminative natures respectively. That is to exploit the similarity function of the RBF kernel to separate the GMM models representing normal and pathological voices. To further improve the separation, we used modified versions of the well known Kullback-leibler and Bhattacharyya distances. The modified distances, unlike the classical ones, do satisfy all metric axioms. As a result, we obtained an improvement of 2 % and 4 % in terms of sensitivity compared to using the classical Kullback-leibler and Bhattacharyya distances respectively. The Receiver Operating Curve (ROC) does illustrate the efficiency of the proposed method

Hand posture recognition using HOW and homogenous kernel

In this paper, we present a static hand gestures recognition system of Arabic Sign Language alphabets. The proposed method uses Histogram Of visual Words (HOW) descriptor and Support Vector Machine (SVM). First, the images of static hand gestures are converted into HOW features and grouped using k-means clustering to create histograms. Then they are converted from non linear space into linear space using Chi-squared kernel. The result is fed into One-vs-All SVM classifier to build signs models. Training and test stages of this technique are implemented on hand postures images using cluttered backgrounds for different lighting conditions, scales and rotations. The proposed method shows a satisfactory recognition rate and achieves good real-time performance regardless of the image resolution.Keywords: arabic sign language - static hand gesture – how - one-vs-all support vector machine (svm

Safe Motion using Viability Kernels

International audienceA prerequisite to safe robot motion is to avoid Inevitable Collision States (ICS). However, the characterization of the ICS set is a challenge. Several approximation methods have been proposed, most of which either are overly conservative or fail to provide proper motion safety guarantees. In order to to improve safety guarantees, we build upon Viability Theory and adapt an algorithm designed to approximate the Viability Kernel, a concept similar to ICS. Our algorithm is applied first to a challenging static environment scenario. It is then extended to handle dynamic environments. Although it is not possible in general to ensure safety forever, we manage nonetheless to achieve infinite motion safety in two special cases

Health Smart Home (HSH): Home Sounds Classification Based on DTW

Abstract-This work is part of CNEPRU ( University research project i