Machine Assisted Analysis of Vowel Length Contrasts in Wolof

Growing digital archives and improving algorithms for automatic analysis of text and speech create new research opportunities for fundamental research in phonetics. Such empirical approaches allow statistical evaluation of a much larger set of hypothesis about phonetic variation and its conditioning factors (among them geographical / dialectal variants). This paper illustrates this vision and proposes to challenge automatic methods for the analysis of a not easily observable phenomenon: vowel length contrast. We focus on Wolof, an under-resourced language from Sub-Saharan Africa. In particular, we propose multiple features to make a fine evaluation of the degree of length contrast under different factors such as: read vs semi spontaneous speech ; standard vs dialectal Wolof. Our measures made fully automatically on more than 20k vowel tokens show that our proposed features can highlight different degrees of contrast for each vowel considered. We notably show that contrast is weaker in semi-spontaneous speech and in a non standard semi-spontaneous dialect.Comment: Accepted to Interspeech 201

American Parisian options

In this article, we describe the various sorts of American Parisian options and propose valuation formulae. Although there is no closed-form valuation for these products in the non-perpetual case, we have been able to reformulate their price as a function of the exercise frontier. In the perpetual case, closed-form solutions or approximations are obtained by relying on excursion theory. We derive the Laplace transform of the first instant Brownian motion reaches a positive level or, without interruption, spends a given amount of time below zero. We perform a detailed comparison of perpetual standard, barrier and Parisian option

Speed perturbation and vowel duration modeling for ASR in Hausa and Wolof languages

International audienceAutomatic Speech Recognition (ASR) for (under-resourced) Sub-Saharan African languages faces several challenges: small amount of transcribed speech, written language normalization issues, few text resources available for language modeling, as well as specific features (tones, morphology, etc.) that need to be taken into account seriously to optimize ASR performance. This paper tries to address some of the above challenges through the development of ASR systems for two Sub-Saharan African languages: Hausa and Wolof. First, we investigate data augmentation technique (through speed perturbation) to overcome the lack of resources. Secondly, the main contribution is our attempt to model vowel length contrast existing in both languages. For reproducible experiments, the ASR systems developed for Hausa and Wolof are made available to the research community on github. To our knowledge, the Wolof ASR system presented in this paper is the first large vocabulary continuous speech recognition system ever developed for this language

Characterization and migration of atmospheric REE in soils and surface waters

Rainwater and snow collected from three different sites in France (Vosges Mountains, French Alps and Strasbourg) show more or less similar shapes of their REE distribution patterns. Rainwater from Strasbourg is the most REE enriched sample, whereas precipitations from the two mountainous, less polluted catchments are less REE enriched and have concentrations close to seawater. They are all strongly LREE depleted. Different water samples from an Alpine watershed comprising snow, interstitial, puddle and streamwater show similar REE distributions with LREE enrichment (rainwater normalized) but MREE and HREE depletion. In this environment, where water transfer from the soil to the river is very quick due to the low thickness of the soils, it appears that REE in streamwater mainly originate from atmospheric inputs. Different is the behaviour of the REE in the spring- and streamwaters from the Vosges Mountains. These waters of long residence time in the deep soil horizons react with soil and bedrock REE carrying minerals and show especially significant negative Eu anomalies compared to atmospheric inputs. Their Sr and Nd isotopic data suggest that most of the Sr and Nd originate from apatite leaching or dissolution. Soil solutions and soil leachates from the upper soil horizons due to alteration processes strongly depleted in REE carrying minerals, have REE distribution patterns close to those of lichens and throughfall. Throughfall is slightly more enriched especially in light REE than filtered rainwater probably due to leaching of atmospheric particles deposited on the foliage and also to leaf excretion. Data suggest that Sr and Nd isotopes of the soil solutions in the upper soil horizons originate from two different sources: 1) An atmospheric source with fertilizer, dust and seawater components and 2) A source mainly determined by mineral dissolution in the soil. These two different sources are also recognizable in the Sr and Nd isotopic composition of the tree’s throughfall solution. The atmospheric contributions of Sr and Nd to throughfall and soil solution are of 20 to 70 and 20%, respectively. In springwater, however, the atmospheric Sr and REE contribution is not detectable

LESSONS LEARNED AFTER DEVELOPMENT AND USE OF A DATA COLLECTION APP FOR LANGUAGE DOCUMENTATION (LIG-AIKUMA)

International audienceLig-Aikuma is a free Android app running on various mobile phones and tablets. It proposes a range of different speech collection modes (recording, respeaking, translation and elicitation) and offers the possibility to share recordings between users. More than 250 hours of speech in 6 different languages from sub-Saharan Africa (including 3 oral languages in the process of being documented) have already been collected with Lig-Aikuma. This paper presents the lessons learned after 3 years of development and use of Lig-Aikuma. While significant data collections were conducted, this has not been done without difficulties. Some mixed results lead us to stress the importance of design choices, data sharing architecture and user manual. We also discuss other potential uses of the app, discovered during its deployment: data collection for language revitalisation, data collection for speech technology development (ASR) and enrichment of existing corpora through the addition of spoken comments

Questions et perspectives de recherche concernant la pauvreté chez les jeunes

Le nombre de jeunes pauvres, âgés de 16 à 24 ans, qui vivent seuls de façon provisoire ou durable, est en progression rapide au Québec. Cette période de la vie est traversée aujourd'hui par de multiples paradoxes allant d'un désir d'autonomie précoce, fondé sur des valeurs modernes d'affirmation de soi et de liberté, à l'allongement de la dépendance, surtout économique, dans un contexte social en mutation. Si les statistiques renseignent sur les caractéristiques de la pauvreté, telles qu'établies à partir des seuils de faible revenu, elles ne permettent toutefois pas de saisir la complexité des situations, des représentations et des stratégies correspondantes. Le rappel de ces données sera suivi de quelques pistes de réflexion qui pourront alimenter éventuellement la recherche et l'action.In Quebec, the number of poor youths, aged 16 to 24, living alone on a temporary or indefinite basis is quickly expanding. This phase of life is nowadays characterized by many a paradox. The range stretches from a nearly quest for autonomy, brought about by modern values such as self-assertion and independence, to prolonged dependency, mainly financial. If statistical data pertaining to poverty are readily available, they do not however display the many faces taken on by poverty as well as the various representations and strategies associated. The underscoring of this confrontation gives way to the examination of different approaches for the study and the eventual circumventing of juvenile poverty

Méthode de calibration des logiciels de microsimulation routière à l'aide de l'optimisation sans dérivées

RÉSUMÉ La modélisation de circulation routière est un outil couramment utilisé en ingénierie des transports afin de prévoir les conséquences de modification au réseau routier ou aux infrastructures de contrôle, ou encore pour évaluer l’impact des fermetures nécessaires aux interventions d’entretien du réseau et de suggérer des mesures de mitigations. Une des familles de logiciels utilisées est celle des logiciels de microsimulation, qui calculent la circulation en décomposant les calculs pour chacun des véhicules présents sur le réseau. Ces logiciels sont flexibles, puisqu’ils permettent aux utilisateurs de choisir les valeurs d’une multitude de paramètres, ce qui permet de les calibrer aux différents comportements routiers observés à travers le monde.----------ABSTRACT Traffic simulation is now a commonly used tool in transportation engineering to assess the impacts of proposed infrastructure, traffic control modifications, and of necessary lane, or road closures, associated with construction sites. Traffic simulation software are divided between families of implemented models and one of them, the microsimulation family, is popular to assess the local impacts of network modifications. Software from the microsimulation family rely on models that simulate individual vehicles, their interactions with each other, and the geometric design of infrastructures, throughout their trips in the studied network. These software are highly flexible since they give practitioners the possibility to modify a large number of parameters, and to calibrate the software to the different driving behaviors observed around the world

Securitization Structures and Security Design

Securitization has been a subject of interest in the security design literature, and various models have been developed in order to explain why such transactions should produce senior securities and junior securities. However securitization structures are far more complex than a simple tranching by seniority. Using a model extending the existing literature, we derive new results by considering that interest and principal should be separately contractible, and that the senior bonds in a securitization should be par-priced, both realistic constraints. This allows us to derive optimal designs closely resembling actual securitization structures. Further, we show that the resecuritization of residuals, in the form of NIMs or reremics, is optimal through a pooling effect. We also analyze the interactions between collateral characteristics and pricing, reflecting securitization execution, and issuer structure choices. With a simple numerical application, we illustrate how important resecuritization is, and also how more attractive an excess-spread structure is relative to a more standard structure, as expected collateral losses increase. According to our analysis, the apparent complexity in excess-spread structure and in resecuritizations can be explained by a valid optimal design argument

Atypical viral and parasitic pattern in Algerian honey bee subspecies Apis mellifera intermissa and A. m. sahariensis

International audienceAbstractUnusually high losses of honey bee colonies are reported in many regions of the world, but little data is available concerning the status of honey bee stocks in Africa. However, the situation on this continent, where beekeeping is weakly developed and where the wild population of the pollinator remains large, can give us an insight on the causes of increased mortalities elsewhere. In this study, we evaluate the health status of Apis mellifera intermissa and A. m. sahariensis populations inhabiting the north and the south of Algeria, respectively. We report few colony losses associated with an atypical pattern of prevalence for common honey bee parasites and pathogens. The presence or absence of these risk factors is discussed in relation to the occurrence of local and global colony losses to contribute to our understanding of how honey bee pathogens and parasite impact this pollinator’s health

Prediction of cognitive decline for enrichment of Alzheimer's disease clinical trials

A key issue to Alzheimer's disease clinical trial failures is poor participant selection. Participants have heterogeneous cognitive trajectories and many do not decline during trials, which reduces a study's power to detect treatment effects. Trials need enrichment strategies to enroll individuals who will decline. We developed machine learning models to predict cognitive trajectories in participants with early Alzheimer's disease (n=1342) and presymptomatic individuals (n=756) over 24 and 48 months respectively. Baseline magnetic resonance imaging, cognitive tests, demographics, and APOE genotype were used to classify decliners, measured by an increase in CDR-Sum of Boxes, and non-decliners with up to 79% area under the curve (cross-validated and out-of-sample). Using these prognostic models to recruit enriched cohorts of decliners can reduce required sample sizes by as much as 51%, while maintaining the same detection power, and thus may improve trial quality, derisk endpoint failures, and accelerate therapeutic development in Alzheimer's disease.Comment: 11 pages, 3 main figures, 3 main tables, supplementary material (3 tables, 2 figures), incorporated feedback from reviewers in the introduction and discussio