Tosca an opera in three acts.

UANL

La circoncision des femmes en Afrique : repenser les politiques de santé

Section des étudiants / Student's section

An ethnolinguistic study of the Yanesha’ (Amuesha) language and speech community in Peru’s Andean Amazon, and the traditional role of Ponapnora, a female rite of passage

Thesis written in co-mentorship with Richard Chase Smith Ph.D, of El Instituto del Bien Comun (IBC) in Peru. The attached file is a pdf created in Word. The pdf file serves to preserve the accuracy of the many linguistic symbols found in the text.

« Et ils prophétiseront » : la prophétie de Jl 3,1-5 reprise en Ac 2, 17-21 : clé d'interprétation du phénomène pentecostal

Cette présente recherche vise à défendre le point de vue selon lequel le don de l’Esprit dans le récit de la Pentecôte (Ac 2, 1-13) s’interprète principalement comme l’investissement d’une puissance habilitant au témoignage. À cette fin, nous posons l’hypothèse que le contenu d’Ac 2, 17-21 est un axe fondamental de la théologie pneumatique de l’œuvre lucanienne, lequel interprète la manifestation pentecostale dans une perspective prophétique. La démonstration se fait par le biais d’une analyse rédactionnelle d’Ac 2, 17-21, une citation de Jl 3,1-5 insérée dans un discours explicatif de Pierre du phénomène pentecostal. Nous examinons d’abord le lieu d’inscription de ce passage dans l’œuvre lucanienne afin d’évaluer la valeur stratégique de son emplacement (chapitre 1). Nous étudions ensuite l’interprétation que fait Luc de cette prophétie pour en venir à la conclusion qu’il envisage l’intervention de l’Esprit essentiellement dans une perspective d’habilitation à la prophétie (chapitre 2). Nous vérifions cette première conclusion dans l’Évangile de Luc (chapitre 3); puis ensuite dans les Actes des Apôtres (chapitre 4). Nous en arrivons ainsi à établir un parallélisme entre les étapes initiatiques du ministère de Jésus dans le troisième évangile et celui des disciples dans les Actes, pour y découvrir que, dans les deux cas, l’effusion de l’Esprit habilite à l’activité prophétique. Le ministère des disciples s’inscrit de la sorte dans le prolongement de celui du Maître. Nous soutenons, en fait, que tout le discours pneumatique de l’Évangile de Luc converge vers l’effusion initiale de l’Esprit sur les disciples dans le récit pentecostal, d’une part, et que cette effusion jette un éclairage sur l’ensemble de l’œuvre missionnaire des Actes, d’autre part. Bref, le passage explicatif du phénomène pentecostal, en l’occurrence Ac 2, 17-21, met en lumière un axe central des perspectives de Luc sur l’Esprit : Il s’agit de l’Esprit de prophétie. Dans cette optique, l’effusion de l’Esprit à la Pentecôte s’interpréterait essentiellement comme l’investissement du croyant d’une puissance en vue du témoignage.

Dessine-moi une maison : psychanalyse d’un processus de design

Cette recherche s’inscrit dans la continuité de celles entreprises en vue d’éclaircir la question du processus de design, et plus spécialement le design architectural de la maison. Elle cherche aussi à développer la réflexivité du designer sur les actes qu’il pose en lui offrant un point de vue depuis l’angle de la psychanalyse. Elle vient rallonger les initiatives amenées par la troisième génération des recherches sur les méthodologies du design en s’intéressant à un volet, jusque-là, peu exploré : le processus inconscient du design architectural. Elle pose comme problématique la question des origines inconscientes du travail créatif chez le concepteur en architecture. La création étant un des sujets importants de la psychanalyse, plusieurs concepts psychanalytiques, comme la sublimation freudienne, l’abordent et tentent de l’expliquer. Le design étant une discipline de création, la psychanalyse peut nous renseigner sur le processus du design, et nous offrir la possibilité de l’observer et de l’approcher. La métaphore architecturale, utilisée pour rendre la théorie freudienne, est aussi le champ d’application de plusieurs théories et concepts psychanalytiques. L’architecture en général, et celle de la maison en particulier, en ce que cette dernière comporte comme investissement émotionnel personnel de la part de son concepteur, constructeur ou utilisateur, offrent un terrain où plusieurs des concepts psychanalytiques peuvent être observés et appliqués. Cette recherche va approcher l’exemple architectural selon les concepts développés par les trois théories psychanalytiques les plus importantes : freudienne, lacanienne et jungienne. L’application de ces concepts se fait par une "autoanalyse" qui met le designer en double posture : celle du sujet de la recherche et celle du chercheur, ce qui favorise hautement la réflexivité voulue. La libre association, une des méthodes de la psychanalyse, sera la première étape qui enclenchera le processus d’autoanalyse et l’accompagnera dans son développement. S’appliquant sur le discours et la forme de la maison, la libre association va chercher à distinguer plusieurs mécanismes psychiques susceptibles d’éclairer notre investigation. Les résultats de l’application des concepts freudiens viendront servir de base pour l’application, par la suite, des concepts de la théorie lacanienne et jungienne. Au terme de cette analyse, nous serions en mesure de présenter une modélisation du processus inconscient du design qui aurait conduit à la création de la maison prise en exemple. Nous découvrirons par cela la nature du processus inconscient qui précède et accompagne le travail créatif du designer. Nous verrons aussi comment ce processus se nourrit des expériences du designer qui remontent jusqu’aux premières années de son enfance. Ceci permettrait de rendre compte de la possibilité d’appliquer les concepts psychanalytiques sur le design architectural et, par ce fait, permettre de déterminer les éventuels façons de concevoir l’apport de la psychanalyse à la pratique de cette discipline qu’est le design ainsi que son enseignement.

Au théâtre on meurt pour rien : essai ; suivi de Le plancher sous la moquette : théâtre.

L’essai Au théâtre on meurt pour rien. Raconter la mort sans coupable, entre Maeterlinck et Chaurette, compare divers usages dramatiques du récit de mort sous l’éclairage de la généalogie nietzschéenne de l’inscription mémorielle. Pour illustrer l’hypothèse d’une fonction classique du témoin de la mort − donner sens au trépas en le situant dans une quête scénique de justice −, l’essai fait appel à des personnages-types chez Eschyle, Shakespeare et Racine. En contraste, des œuvres du dramaturge moderne Maeterlinck (Intérieur) et du dramaturge contemporain Normand Chaurette (Fragments d’une lettre d’adieu lus par des géologues, Stabat Mater II) sont interprétées comme logeant toute leur durée scénique dans un temps de la mort qui dépasserait la recherche d’un coupable absolu ; une étude approfondie les distingue toutefois par la valeur accordée à l’insolite et à la banalité, ainsi qu’à la singularité des personnages. Le plancher sous la moquette est une pièce de théâtre en trois scènes et trois registres de langue, pour deux comédiennes. Trois couples de sœurs se succèdent dans le salon d’un appartement, jadis une agence de détective qui a marqué leur imaginaire d’enfant. Thématiquement, la pièce déplace le lien propre aux films noirs entre l’enquête et la ville, en y juxtaposant le brouillage temporel qu’implique l’apparition de fantômes. Chacune des trois scènes déréalise les deux autres en redistribuant les mêmes données selon une tonalité autre, mais étrangement similaire, afin d’amener le spectateur à douter du hors-scène : le passé, l’appartement, Montréal. Son réflexe cartésien de traquer la vérité doit le mener à découvrir que les scènes ne vont pas de l’ombre à la lumière, mais qu’elles montrent plutôt que dans l’une et l’autre, la mort n’échappe pas aux trivialités de la mémoire.

Comparing the Protests of Undocumented Migrants Beyond Contexts: Collective Actions as Acts of Emancipation

In this article, we demonstrate that the collective actions of undocumented migrants possess similar symbolic dimensions, even if the contexts of their actions differ. We explain this finding by focusing on the power relations that undocumented migrants face. Given that they occupy a very specific position in society (i.e., they are neither included in nor completely excluded from citizenship), they experience similar forms of power relations vis-à-vis public authorities in different countries. We argue that this leads them to participate in collective actions as acts of emancipation. Our analysis illustrates this argument by comparing marches by undocumented migrants in three countries: France, Germany and Canada-Quebec. Through an in-depth analysis, we demonstrate that these marches redefine the legal order and politicize the presence of undocumented migrants in the public sphere. By highlighting the cognitive, emotional and relational dimensions of collective actions, we show that the symbolic dimension of these three marches relates to the empowerment, pride and solidarity of undocumented migrants.

Speech Analysis using Modern Techniques of Nonlinear Dynamics

Medical fields requires fast, simple and noninvasive methods of diagnostic techniques. Several methods are available and possible because of the growth of technology that provides the necessary means of collecting and processing signals. The present thesis details the work done in the field of voice signals. New methods of analysis have been developed to understand the complexity of voice signals, such as nonlinear dynamics aiming at the exploration of voice signals dynamic nature. The purpose of this thesis is to characterize complexities of pathological voice from healthy signals and to differentiate stuttering signals from healthy signals. Efficiency of various acoustic as well as non linear time series methods are analysed. Three groups of samples are used, one from healthy individuals, subjects with vocal pathologies and stuttering subjects. Individual vowels/ and a continuous speech data for the utterance of the sentence "iruvarum changatimaranu" the meaning in English is "Both are good friends" from Malayalam language are recorded using a microphone . The recorded audio are converted to digital signals and are subjected to analysis.Acoustic perturbation methods like fundamental frequency (FO), jitter, shimmer, Zero Crossing Rate(ZCR) were carried out and non linear measures like maximum lyapunov exponent(Lamda max), correlation dimension (D2), Kolmogorov exponent(K2), and a new measure of entropy viz., Permutation entropy (PE) are evaluated for all three groups of the subjects. Permutation Entropy is a nonlinear complexity measure which can efficiently distinguish regular and complex nature of any signal and extract information about the change in dynamics of the process by indicating sudden change in its value. The results shows that nonlinear dynamical methods seem to be a suitable technique for voice signal analysis, due to the chaotic component of the human voice. Permutation entropy is well suited due to its sensitivity to uncertainties, since the pathologies are characterized by an increase in the signal complexity and unpredictability. Pathological groups have higher entropy values compared to the normal group. The stuttering signals have lower entropy values compared to the normal signals.PE is effective in charaterising the level of improvement after two weeks of speech therapy in the case of stuttering subjects. PE is also effective in characterizing the dynamical difference between healthy and pathological subjects. This suggests that PE can improve and complement the recent voice analysis methods available for clinicians. The work establishes the application of the simple, inexpensive and fast algorithm of PE for diagnosis in vocal disorders and stuttering subjects.

Speech sample estimation from composite zerocrossings and encoding via adaptive switching of transforms

This thesis investigates the potential use of zerocrossing information for speech sample estimation. It provides 21 new method tn) estimate speech samples using composite zerocrossings. A simple linear interpolation technique is developed for this purpose. By using this method the A/D converter can be avoided in a speech coder. The newly proposed zerocrossing sampling theory is supported with results of computer simulations using real speech data. The thesis also presents two methods for voiced/ unvoiced classification. One of these methods is based on a distance measure which is a function of short time zerocrossing rate and short time energy of the signal. The other one is based on the attractor dimension and entropy of the signal. Among these two methods the first one is simple and reguires only very few computations compared to the other. This method is used imtea later chapter to design an enhanced Adaptive Transform Coder. The later part of the thesis addresses a few problems in Adaptive Transform Coding and presents an improved ATC. Transform coefficient with maximum amplitude is considered as ‘side information’. This. enables more accurate tfiiz assignment enui step—size computation. A new bit reassignment scheme is also introduced in this work. Finally, sum ATC which applies switching between luiscrete Cosine Transform and Discrete Walsh-Hadamard Transform for voiced and unvoiced speech segments respectively is presented. Simulation results are provided to show the improved performance of the coder

Development of a Biometric Personal Authentication System Based on Fingerprint and Speech

Biometrics deals with the physiological and behavioral characteristics of an individual to establish identity. Fingerprint based authentication is the most advanced biometric authentication technology. The minutiae based fingerprint identification method offer reasonable identification rate. The feature minutiae map consists of about 70-100 minutia points and matching accuracy is dropping down while the size of database is growing up. Hence it is inevitable to make the size of the fingerprint feature code to be as smaller as possible so that identification may be much easier. In this research, a novel global singularity based fingerprint representation is proposed. Fingerprint baseline, which is the line between distal and intermediate phalangeal joint line in the fingerprint, is taken as the reference line. A polygon is formed with the singularities and the fingerprint baseline. The feature vectors are the polygonal angle, sides, area, type and the ridge counts in between the singularities. 100% recognition rate is achieved in this method. The method is compared with the conventional minutiae based recognition method in terms of computation time, receiver operator characteristics (ROC) and the feature vector length. Speech is a behavioural biometric modality and can be used for identification of a speaker. In this work, MFCC of text dependant speeches are computed and clustered using k-means algorithm. A backpropagation based Artificial Neural Network is trained to identify the clustered speech code. The performance of the neural network classifier is compared with the VQ based Euclidean minimum classifier. Biometric systems that use a single modality are usually affected by problems like noisy sensor data, non-universality and/or lack of distinctiveness of the biometric trait, unacceptable error rates, and spoof attacks. Multifinger feature level fusion based fingerprint recognition is developed and the performances are measured in terms of the ROC curve. Score level fusion of fingerprint and speech based recognition system is done and 100% accuracy is achieved for a considerable range of matching threshold

Modified Block Adaptive Predictive Coder For Speech Processing

This thesis investigated the potential use of Linear Predictive Coding in speech communication applications. A Modified Block Adaptive Predictive Coder is developed, which reduces the computational burden and complexity without sacrificing the speech quality, as compared to the conventional adaptive predictive coding (APC) system. For this, changes in the evaluation methods have been evolved. This method is as different from the usual APC system in that the difference between the true and the predicted value is not transmitted. This allows the replacement of the high order predictor in the transmitter section of a predictive coding system, by a simple delay unit, which makes the transmitter quite simple. Also, the block length used in the processing of the speech signal is adjusted relative to the pitch period of the signal being processed rather than choosing a constant length as hitherto done by other researchers. The efficiency of the newly proposed coder has been supported with results of computer simulation using real speech data. Three methods for voiced/unvoiced/silent/transition classification have been presented. The first one is based on energy, zerocrossing rate and the periodicity of the waveform. The second method uses normalised correlation coefficient as the main parameter, while the third method utilizes a pitch-dependent correlation factor. The third algorithm which gives the minimum error probability has been chosen in a later chapter to design the modified coder The thesis also presents a comparazive study beh-cm the autocorrelation and the covariance methods used in the evaluaiicn of the predictor parameters. It has been proved that the azztocorrelation method is superior to the covariance method with respect to the filter stabf-it)‘ and also in an SNR sense, though the increase in gain is only small. The Modified Block Adaptive Coder applies a switching from pitch precitzion to spectrum prediction when the speech segment changes from a voiced or transition region to an unvoiced region. The experiments cont;-:ted in coding, transmission and simulation, used speech samples from .\£=_‘ajr2_1a:r1 and English phrases. Proposal for a speaker reecgnifion syste: and a phoneme identification system has also been outlized towards the end of the thesis.

COMBINED FEATURE EXTRACTION TECHNIQUES AND NAIVE BAYES CLASSIFIER FOR SPEECH RECOGNITION

Speech processing and consequent recognition are important areas of Digital Signal Processing since speech allows people to communicate more natu-rally and efficiently. In this work, a speech recognition system is developed for re-cognizing digits in Malayalam. For recognizing speech, features are to be ex-tracted from speech and hence feature extraction method plays an important role in speech recognition. Here, front end processing for extracting the features is per-formed using two wavelet based methods namely Discrete Wavelet Transforms (DWT) and Wavelet Packet Decomposition (WPD). Naive Bayes classifier is used for classification purpose. After classification using Naive Bayes classifier, DWT produced a recognition accuracy of 83.5% and WPD produced an accuracy of 80.7%. This paper is intended to devise a new feature extraction method which produces improvements in the recognition accuracy. So, a new method called Dis-crete Wavelet Packet Decomposition (DWPD) is introduced which utilizes the hy-brid features of both DWT and WPD. The performance of this new approach is evaluated and it produced an improved recognition accuracy of 86.2% along with Naive Bayes classifier.

PERFORMANCE OF DIFFERENT CLASSIFIERS IN SPEECH RECOGNITION

Speech is the most natural means of communication among human beings and speech processing and recognition are intensive areas of research for the last five decades. Since speech recognition is a pattern recognition problem, classification is an important part of any speech recognition system. In this work, a speech recognition system is developed for recognizing speaker independent spoken digits in Malayalam. Voice signals are sampled directly from the microphone. The proposed method is implemented for 1000 speakers uttering 10 digits each. Since the speech signals are affected by background noise, the signals are tuned by removing the noise from it using wavelet denoising method based on Soft Thresholding. Here, the features from the signals are extracted using Discrete Wavelet Transforms (DWT) because they are well suitable for processing non-stationary signals like speech. This is due to their multi- resolutional, multi-scale analysis characteristics. Speech recognition is a multiclass classification problem. So, the feature vector set obtained are classified using three classifiers namely, Artificial Neural Networks (ANN), Support Vector Machines (SVM) and Naive Bayes classifiers which are capable of handling multiclasses. During classification stage, the input feature vector data is trained using information relating to known patterns and then they are tested using the test data set. The performances of all these classifiers are evaluated based on recognition accuracy. All the three methods produced good recognition accuracy. DWT and ANN produced a recognition accuracy of 89%, SVM and DWT combination produced an accuracy of 86.6% and Naive Bayes and DWT combination produced an accuracy of 83.5%. ANN is found to be better among the three methods.

Speech Recognition of Malayalam Numbers

Digit speech recognition is important in many applications such as automatic data entry, PIN entry, voice dialing telephone, automated banking system, etc. This paper presents speaker independent speech recognition system for Malayalam digits. The system employs Mel frequency cepstrum coefficient (MFCC) as feature for signal processing and Hidden Markov model (HMM) for recognition. The system is trained with 21 male and female voices in the age group of 20 to 40 years and there was 98.5% word recognition accuracy (94.8% sentence recognition accuracy) on a test set of continuous digit recognition task.

Development & evaluation of different acoustic models for Malayalam continuous speech recognition

Performance of any continuous speech recognition system is dependent on the accuracy of its acoustic model. Hence, preparation of a robust and accurate acoustic model lead to satisfactory recognition performance for a speech recognizer. In acoustic modeling of phonetic unit, context information is of prime importance as the phonemes are found to vary according to the place of occurrence in a word. In this paper we compare and evaluate the effect of context dependent tied (CD tied) models, context dependent (CD) and context independent (CI) models in the perspective of continuous speech recognition of Malayalam language. The database for the speech recognition system has utterance from 21 speakers including 11 female and 10 males. Our evaluation results show that CD tied models outperforms CI models over 21%.