University of Avignon

About: University of Avignon is a education organization based out in Avignon, Provence-Alpes-Côte-d'Azur, France. It is known for research contribution in the topics: Population & Speaker recognition. The organization has 1526 authors who have published 3766 publications receiving 88928 citations.

Optimality Conditions for C1,1 Constrained Multiobjective Problems

Abstract: The present paper is concerned with the study of the optimality conditions for constrained multiobjective programming problems in which the data have locally Lipschitz Jacobian maps. Second-order necessary and sufficient conditions for efficient solutions are established in terms of second-order subdifferentials of vector functions.

DiSeg 1.0: The first system for Spanish discourse segmentation

Abstract: Nowadays discourse parsing is a very prominent research topic. However, there is not a discourse parser for Spanish texts. The first stage in order to develop this tool is discourse segmentation. In this work, we present DiSeg, the first discourse segmenter for Spanish, which uses the framework of Rhetorical Structure Theory and is based on lexical and syntactic rules. We describe the system and we evaluate its performance against a gold standard corpus, divided in a medical and a terminological subcorpus. We obtain promising results, which means that discourse segmentation is possible using shallow parsing.

Comparison and Combination of Lightly Supervised Approaches for Language Portability of a Spoken Language Understanding System

Abstract: Portability of a spoken dialogue system (SDS) to a new domain or a new language is a hot topic as it may imply gains in time and cost for building new SDSs. In particular in this paper we investigate several fast and efficient approaches for language portability of the spoken language understanding (SLU) module of a dialogue system. We show that the use of statistical machine translation (SMT) can reduce the time and the cost of porting a system from a source to a target language. For conceptual decoding, a state-of-the-art module based on conditional random fields (CRF) is used and a new approach based on phrase-based statistical machine translation (PB-SMT) is also evaluated. The experimental results show the efficiency of the proposed methods for a fast and low cost SLU language portability. In addition, we propose two methods to increase SLU robustness to translation errors. Overall, it is shown that the combination of all these approaches can further reduce the concept error rate. While most of the experiments in this paper deal with portability from French to Italian (given the availability of the Media French corpus and its subset manually translated into Italian), a validation of our methodology is eventually proposed in Arabic.

On the Distance Spectrum Assignment in Elastic Optical Networks

Abstract: In elastic optical networks, two lightpaths sharing common fiber links might have to be isolated in the spectrum domain with a proper guard-band to prevent crosstalk and/or reduce physical-layer security threats. Meanwhile, the actual requirements on guard-band sizes can vary for different lightpath pairs, because of various reasons. Therefore, in this paper, we consider the situation in which the actual guard-band requirements for different lightpath pairs are different, and formulate the distance spectrum assignment (DSA) problem to investigate how to assign the spectrum resources efficiently in such a situation. We first define the DSA problem formally and prove its $\mathcal {NP}$ -hardness and inapproximability. Then, we analyze and provide the upper and lower bounds for the optimal solution of DSA, and prove that they are tight. In order to solve the DSA problem time-efficiently, we develop a two-phase algorithm. In its first phase, we obtain an initial solution and then the second phase improves the quality of the initial solution with random optimization. We prove that the proposed two-phase algorithm can get the optimal solution in bipartite DSA conflict graphs and can ensure an approximate ratio of $\mathcal {O}(\log (|V|))$ in complete DSA conflict graphs, where $|V|$ is the number of vertices in the conflict graph, i.e. , the number of lightpaths to be considered. Numerical results demonstrate our proposed algorithm can find near-optimal solutions for DSA in various conflict graphs.