La ville de Lubumbashi connaît une situation complexe caractérisée par la coexistence de nombreuses langues qui se partagent le marché linguistique : les langues ethniques à vocation identitaire et d’usage limité, les langues nationales à fonction véhiculaire et le français langue officielle parlée par une partie réduite des citadins. Dans un contexte de plurilinguisme, il est intéressant de connaître la valeur de chaque langue auprès de ses locuteurs. Sur le terrain on observe une opposition entre locuteurs non francophones et francophones et parmi ces derniers entre locuteurs scolarisés et locuteurs ayant appris le français « sur le tas ». Dans un contexte de « diglossie », les langues donnent lieu à des représentations contrastées qui interfèrent sur leur pratique effective. Notre recherche vise à décrire à la fois les usages et les attitudes linguistiques qui leur sont corrélées. Pour ce faire, nous sollicitons divers modèles, à la fois le modèle labovien adapté à l’environnement urbain pour évaluer quantitativement le degré de sécurité /insécurité linguistique, et celui du variationnisme développant des analyses plus qualitatives. Du point de vue de la méthodologie de l'enquête, notre population d'enquête a été construite à partir de différentes variables ou de traits classificatoires. La technique du questionnaire (questions ouvertes et questions fermées) a invité les élèves à livrer leurs pratiques et leurs représentations linguistiques. Les entretiens de type semi-dirigés sont des dispositifs que nous utilisons auprès des enquêtés adultes afin d'accéder à leurs représentations linguistiques. / The town of Lubumbashi lives a complex situation characterized by the coexistence of numerous languages sharing the same linguistic market: the ethnic language with the identity vocation and with limited usage, national language with a vehicular function and the official French language spoken by a reduced number of city-dwellers. In the context of multilinguism, it is interesting to know the value of each language beside its speakers. In the field we observe an opposition between the speakers and non-French-speakers and French- speakers, and among the latter between educated speakers and speakers having learnt French “on the Job training”. In a context of “diglossy,” the languages generate the contrasted representations which interfere practically on their effective practice. Our research aims at describing at the same time the usages and the linguistic attitudes which are correlated with them. Therefore, we require diverse models, at the same time the model labovien adapted to the urban environment to evaluate quantitatively the degree of linguistic security/insecurity, and the one of variationism developing more quantitative analyses. Concerning the methodology of investigation, our sample population has been constituted from different variables or classificatory features. The technique of the questionnaire (opened and closed questions) has invited pupils to provide their practice and their linguistic representations. The conversations of the type semi-conducted are the dispositive that we use towards the investigations of adults in order to get their linguistic representations.

This thesis presents a novel Dynamic Gesture Language Recognition (DGLR) system for human-robot and inter-robot communication. We developed and implemented an experimental setup consisting of a humanoid robot/android able to recognize and execute in real time all the arm gestures of the Dynamic Gesture Language (DGL) in similar way as humans do. Our DGLR system comprises two main subsystems: an image processing (IP) module and a linguistic recognition system (LRS) module. The IP module enables recognizing individual DGL gestures. In this module, we use the bag-of-features (BOFs) and a local part model approach for dynamic gesture recognition from images. Dynamic gesture classification is conducted using the BOFs and nonlinear support-vector-machine (SVM) methods. The multiscale local part model preserves the temporal context. The IP module was tested using two databases, one consisting of images of a human performing a series of dynamic arm gestures under different environmental conditions and a second database consisting of images of an android performing the same series of arm gestures. The linguistic recognition system (LRS) module uses a novel formal grammar approach to accept DGL-wise valid sequences of dynamic gestures and reject invalid ones. LRS consists of two subsystems: one using a Linear Formal Grammar (LFG) to derive the valid sequence of dynamic gestures and another using a Stochastic Linear Formal Grammar (SLFG) to occasionally recover gestures that were unrecognized by the IP module. Experimental results have shown that the DGLR system had a slightly better overall performance when recognizing gestures made by a human subject (98.92% recognition rate) than those made by the android (97.42% recognition rate).