Bilingual Learning of Multi-sense Embeddings with Discrete Autoencoders

We present an approach to learning multi-sense word embeddings relying both on monolingual and bilingual information. Our model consists of an encoder, which uses monolingual and bilingual context (i.e. a parallel sentence) to choose a sense for a given word, and a decoder which predicts context words based on the chosen sense. The two components are estimated jointly. We observe that the word representations induced from bilingual data outperform the monolingual counterparts across a range of evaluation tasks, even though crosslingual information is not available at test time

Trapping dust particles in the outer regions of protoplanetary disks

In order to explain grain growth to mm sized particles and their retention in outer regions of protoplanetary disks, as it is observed at sub-mm and mm wavelengths, we investigate if strong inhomogeneities in the gas density profiles can slow down excessive radial drift and can help dust particles to grow. We use coagulation/fragmentation and disk-structure models, to simulate the evolution of dust in a bumpy surface density profile which we mimic with a sinusoidal disturbance. For different values of the amplitude and length scale of the bumps, we investigate the ability of this model to produce and retain large particles on million years time scales. In addition, we introduced a comparison between the pressure inhomogeneities considered in this work and the pressure profiles that come from magnetorotational instability. Using the Common Astronomy Software Applications ALMA simulator, we study if there are observational signatures of these pressure inhomogeneities that can be seen with ALMA. We present the favorable conditions to trap dust particles and the corresponding calculations predicting the spectral slope in the mm-wavelength range, to compare with current observations. Finally we present simulated images using different antenna configurations of ALMA at different frequencies, to show that the ring structures will be detectable at the distances of the Taurus Auriga or Ophiucus star forming regions.Comment: Pages 15, Figures 14. Accepted for publication in Astronomy and Astrophysic

Global Analysis of Quorum Sensing Targets in the Intracellular Pathogen Brucella melitensis 16 M

Many pathogenic bacteria use a regulatory process termed quorum sensing (QS) to produce and detect small diffusible molecules to synchronize gene expression within a population. In Gram-negative bacteria, the detection of, and response to, these molecules depends on transcriptional regulators belonging to the LuxR family. Such a system has been discovered in the intracellular pathogen Brucella melitensis, a Gram-negative bacterium responsible for brucellosis, a worldwide zoonosis that remains a serious public health concern in countries were the disease is endemic. Genes encoding two LuxR-type regulators, VjbR and BabR, have been identified in the genome of B. melitensis 16 M. A DeltavjbR mutant is highly attenuated in all experimental models of infection tested, suggesting a crucial role for QS in the virulence of Brucella. At present, no function has been attributed to BabR. The experiments described in this report indicate that 5% of the genes in the B. melitensis 16 M genome are regulated by VjbR and/or BabR, suggesting that QS is a global regulatory system in this bacterium. The overlap between BabR and VjbR targets suggest a cross-talk between these two regulators. Our results also demonstrate that VjbR and BabR regulate many genes and/or proteins involved in stress response, metabolism, and virulence, including those potentially involved in the adaptation of Brucella to the oxidative, pH, and nutritional stresses encountered within the host. These findings highlight the involvement of QS as a major regulatory system in Brucella and lead us to suggest that this regulatory system could participate in the spatial and sequential adaptation of Brucella strains to the host environment.Journal ArticleResearch Support, Non-U.S. Gov'tSCOPUS: ar.jinfo:eu-repo/semantics/publishe

Microplanning with Communicative Intentions: The SPUD System

The process of microplanning in Natural Language Generation (NLG) encompasses a range of problems in which a generator must bridge underlying domain-specific representations and general linguistic representations. These problems include constructing linguistic referring expressions to identify domain objects, selecting lexical items to express domain concepts, and using complex linguistic constructions to concisely convey related domain facts. In this paper, we argue that such problems are best solved through a uniform, comprehensive, declarative process. In our approach, the generator directly explores a search space for utterances described by a linguistic grammar. At each stage of search, the generator uses a model of interpretation, which characterizes the potential links between the utterance and the domain and context, to assess its progress in conveying domain-specific representations. We further address the challenges for implementation and knowledge representation in this approach. We show how to implement this approach effectively by using the lexicalized tree-adjoining grammar formalism (LTAG) to connect structure to meaning and using modal logic programming to connect meaning to context. We articulate a detailed methodology for designing grammatical and conceptua

Independent Parallelism in Finite Copying Parallel Rewriting Systems

We consider the class of parallel rewriting systems and investigate the interaction between two complexity measures, that in the literature have been called synchronized parallelism and independent parallelism. It is shown that, when the degree of synchronized parallelism is bounded by some constant greater than one, the degree of independent parallelism induces an infinite non-collapsing hierarchy within the family of generated languages. The result is obtained using an original characterization of parallel rewriting systems. Other language-theoretic properties of parallel rewriting systems are proved in this work, that together with our main result provide an answer to some questions that were left open in the literature

Contrast in concept-to-speech generation

In concept-to-speech systems, spoken output is generated on the basis of a text that has been produced by the system itself. In such systems, linguistic information from the text generation component may be exploited to achieve a higher prosodic quality of the speech output than can be obtained in a plain text-to-speech system. In this paper we discuss how information from natural language generation can be used to compute prosody in a concept-to-speech system, focusing on the automatic marking of contrastive accents on the basis of information about the preceding discourse. We discuss and compare some formal approaches to this problem and present the results of a small perception experiment that was carried out to test which discourse contexts trigger a preference for contrastive accent, and which do not. Finally, we describe a method for marking contrastive accent in a generic concept-to-speech system called D2S. In D2S, contrastive accent is assigned to generated phrases expressing different aspects of similar events. Unlike in previous approaches, there is no restriction on the kind of entities that may be considered contrastive. This is in line with the observation that, given the ‘right' context, any two items may stand in contrast to each other