A machine learning approach for digital image restoration

This paper illustrates the process of image restoration in the sense of detecting images within a scanned document such as a photo album or scrapbook. The primary use case of this research is to accelerate the cropping process for the employees of Cinetis, a company based in Martigny, Switzerland that specializes in the digitalization of old media formats. In this paper, we will first summarize the state of the art in this field of research. This will include explanations of various techniques and algorithms involved with feature and document detection used by various digital companies

Evaluation of the photovoltaic power plant of the GridLab

In der vorliegenden Bachelorarbeit wird eine Software beziehungsweise ein Überwa- chungssystem für die Fachhochschule HES-SO in Sion implementiert. Mithilfe dieses Über-wachungssystems kann die produzierte Energie der Photovoltaikanlage am Gebäude der HES-SO Sion grafisch angezeigt werden

Ajout d'une fonctionnalité de prédiction de phrases par apprentissage à un logiciel d'aide à la correction pour les dyslexiques

Depuis l’apparition des premiers claviers, l’homme a toujours cherché à augmenter sa vitesse de frappe pour gagner en productivité. Ce gain représente un impact significatif pour les personnes écrivant de manière quotidienne sur des claviers (qu’ils soient virtuels ou non) ou pour les personnes souffrant de troubles de l’écriture comme la dyslexie. Dans ce travail nous avons étudié de manière comparative les différentes applications et outils existants oeuvrant principalement dans les domaines de l’autocomplétion et de la prédiction de phrase. Nous avons constaté que bien que ceux-ci fournissent des résultats déjà exploitables, ils ne prenaient que peu ou pas en compte le vocabulaire propre à l’utilisateur

Reconnaissance et transformation de locuteurs

This PhD thesis tries to understand how to analyse, decompose, model and transform the vocal identity of a human when seen through an automatic speaker recognition application. It starts with an introduction explaining the properties of the speech signal and the basis of the automatic speaker recognition. Then, the errors of an operating speaker recognition application are analysed. From the deficiencies and mistakes noticed in the running application, some observations cm be made which will imply a re-evaluation of the characteristic parameters of a speaker, and to reconsider some parts of the automatic speaker recognition chain. In order to determine what are the characterising parameters of a speaker, these are extracted from the speech signal with an analysis and synthesis harmonic plus noise model (H+N). The analysis and re-synthesis of the harmonic and noise parts indicate those which are speech or speaker dependent. It is then shown that the speaker discriminating information can be found in the residual of the subtraction from the original signal of the H+N modeled signal. Then, a study of the impostors phenomenon, essential in the tuning of a speaker recognition system, is carried out. The impostors are simulated in two ways: first by a transformation of the speech of a source speaker (the impostor) to the speech of a target speaker (the client) using the parameters extracted from the H+N model. This way of transforming the parameters is efficient as the false acceptance rate grows from 4% to 23%. Second, an automatic imposture by speech sepent concatenation is carried out. In this case the false acceptance rate grows to 30%. A way to become less sensitive to the spectral modification impostures is to remove the harmonic part or even the noise part modeled by the H+N from the original signal. Using such a subtraction decreases the false acceptance rate to 8% even if transformed impostors are used. To overcome the lack of training data — one of the main cause of modeling errors in speaker recognition — a decomposition of the recognition task into a set of binary classifiers is proposed. A classifier matrix is built and each of its elements has to classify word by word the data coming from the client and another speaker (named here an anti-speaker, randomly chosen from an extemal database). With such an approach it is possible to weight the results according to the vocabulary or the neighbours of the client in the parameter (acoustic) space. The output of the mamx classifiers are then weighted and mixed in order to produce a single output score. The weights are estimated on validation data, and if the weighting is done properly, the binary pair speaker recognition system gives better results than a state of the an HMM based system. In order to set a point of operation (i.e. a point on the COR cuwe) for the speaker recognition application, an a priori threshold has to be determined. Theoretically the threshold should be speaker independent when stochastic models are used. However, practical experiments show that this is not the case, as due to modeling mismatch the threshold becomes speaker and utterance length dependant. A theoretical framework showing how to adjust the threshold using the local likelihood ratio is then developed. Finally, a last modeling error correction method using decision fusion is proposed. Some practical experiments show the advantages and drawbacks of the fusion approach in speaker recognition applications

Likelihood ratio adjustment for the compensation of model mismatch in speaker verification

Cet article présente une méthode d'ajustement des seuils de vérification du locuteur basée sur un modèle Gaussien des distributions du logarithme du rapport de vraisemblance. L'article expose les hypothèses sous lesquelles ce modèle est valide, indique plusieurs méthodes d'ajustement des seuils, et en illustre les apports et les limites par des expériences de vérification sur une base de données de 20 locuteurs

Browser RERO DOC

L’objectif de ce travail est de remplacer le navigateur existant sur www.doc.rero.ch qui permet de consulter documents PDF, des images tels que des thèses, des livres, etc. Pour atteindre cet objectif, l’état de l’art des solutions pour la manipulation d’images et des PDF a été réalisé

Solder assembly of cantilever bar force or displacement sensors

In this paper, the stability of a displacement sensor assembled with Sn96 (tin- silver) solder, Sn62 (tin-leadsilver) solder or conductive silver-loaded epoxy glue was compared. In the absence of humidity or thermal cycling, the glue was found to be much better than both solders. This is ascribed to better creep behaviour combined with lower elastic modulus and much smaller bond thickness. However, the glue underwent severe degradation in hot, humid air, and is therefore not suitable for all applications. Among the solder alloys, high temperature Sn96 exhibited higher stability than the standard Sn62, in accordance with expectations

1997 NIST Evaluation: Text independent speaker detection (verification)

Every year the US government institute {NIST} (National Institute for Standardization and Technologies) organize a speaker verification/ identification evaluation. Any research institute can participate. In 1997 IDIAP choosed to participate in collaboration with ENST (Paris/France). The common part of the IDIAP and ENST system was the threshold calculator, and the first tests on GMM systems. The folowing document will describe the IDIAP system an how to find information usfull for participating to the next NIST evaluations. The access to the html version of the file is limited

Text dependent speaker verification using binary classifiers

This paper describes how a speaker verification task can be advantageously decomposed into a series of binary classification problems, i.e. each problem discriminating between two classes only. Each binary classifier is specific to one speaker, one anti-speaker and one word. Decision trees dealing classifiers. The set of classifiers is then pruned to eliminate the less relevant ones. Diverse pruning methods are experimented, and it is shown that when the speaker verification decision is performed with an a priori threshold, some of them give better results than a reference HMM system

Combining methods to improve speaker verification decision

The aim of this paper is to describe how the combination of speaker verification algorithms with a priori decision thresholds can improve the overall robustness of a real application. The evaluation is performed in the context of a field application where each client is verified from a 7 digit pin code. This paper demonstrate that it is possible to increase the global performances of the system on combining the result of several algorithms