Visualisation de Traces d’Exécution et Limite de Perception

National audienceL’analyse de données temporelles est transversale `àde nombreux domaines (e.g. médical, finance, météorlogie, industriel, ). Ces données sont aujourd’hui générées en grandes quantités par de multiples sources pouvant être de natures très hétéogènes. Le but recherché en analysant des données temporelles est de d´ecouvrir un comportement permettant d’établir un modèle (e.g. météorlogique, finance) et d’identifier des comportements anormaux, ou des erreurs dans les données. L’identification d’outliers peut se faire à l’aide d’algorithmes de fouille de donn´ees ou avec des outils de visualisation

End-User-Development for Smart Homes: Relevance and Challenges

International audienceUbiquitous computing is now mature enough to unleash the potential of Smart Homes. The obstacle is no more about hardware concerns but lies in how inhabitants can build, configure and control their Smart Home. In this paper, we defend the idea that End-User-Development (EUD), which considers inhabitants as makers rather than mere consumers, is an effective approach for tackling this obstacle. We reflect on the lifecycle of devices and services to discuss challenges that EUD system will have to address in the Smart Home context: installation and maintenance, designation, control, development (including programming, testing, and reusing), and sharing

Analyse et créativité pour la conception d'interaction avec l'habitat intelligent

International audienceConcevoir des interactions pour des systèmes innovants implique une première étape dans laquelle se mêlent découverte du domaine et des contraintes, créativité et mise en situation des idées sélectionnées. Cette étape a pour objectif de s'engager avec plus de confiance dans le processus de conception. Nous exposons ici une partie de notre démarche sur de nouvelles interactions avec l'habitat intelligent. Nous avons cherché à répondre le plus efficacement à nos différents objectifs par l'association de pratiques complémentaires que nous présentons succinctement avec un retour d'expérience sur leur mise en application et leur enchaînement

Connecting content and logical words

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Knowing How You Know: Toddlers Reevaluate Words Learned From an Unreliable Speaker

There has been little investigation of the way source monitoring, the ability to track the source of one’s knowledge, may be involved in lexical acquisition. In two experiments, we tested whether toddlers (mean age 30 months) can monitor the source of their lexical knowledge and reevaluate their implicit belief about a word mapping when this source is proven to be unreliable. Experiment 1 replicated previous research (Koenig & Woodward, 2010): children displayed better performance in a word learning test when they learned words from a speaker who has previously revealed themself as reliable (correctly labeling familiar objects) as opposed to an unreliable labeler (incorrectly labeling familiar objects). Experiment 2 then provided the critical test for source monitoring: children first learned novel words from a speaker before watching that speaker labeling familiar objects correctly or incorrectly. Children who were exposed to the reliable speaker were significantly more likely to endorse the word mappings taught by the speaker than children who were exposed to a speaker who they later discovered was an unreliable labeler. Thus, young children can reevaluate recently learned word mappings upon discovering that the source of their knowledge is unreliable. This suggests that children can monitor the source of their knowledge in order to decide whether that knowledge is justified, even at an age where they are not credited with the ability to verbally report how they have come to know what they know

How well do models of cross-situational word learning account for the learning of ambiguous words?

Existing theories of word learning largely focus on a learner's ability to learn a single meaning for a word despite the fact that many words have multiple meanings. Several computational models of cross-situational word learning have been proposed to explain how words are learned, but it is unknown to what extent they can learn ambiguous words with multiple meanings. Here, we present an experiment showing that adult learners are able to learn multiple meanings of novel ambiguous words in a cross-situational word learning paradigm, and are especially good at doing so when the meanings of the words are related (polysemous) rather than unrelated (homophonous). We evaluated the ability of ten different computational models of cross-situational word learning to explain the empirical data, and none were able to learn the ambiguous words as successfully as the adult learners. Moreover, because these computational models do not represent any semantic information, they are in principle unable to replicate the key difference between polysemous and homophonous word learning found in the study

Competition and symmetry in an artificial word learning task

Natural language involves competition. The sentences we choose to utter activate alternative sentences (those we chose not to utter), which hearers typically infer to be false. Hence, as a first approximation, the more alternatives a sentence activates, the more inferences it will trigger. But a closer look at the theory of competition shows that this is not quite true and that under specific circumstances, so-called symmetric alternatives cancel each other out. We present an artificial word learning experiment in which participants learn words that may enter into competition with one another. The results show that a mechanism of competition takes place, and that the subtle prediction that alternatives trigger inferences, and may stop triggering them after a point due to symmetry, is borne out. This study provides a minimal testing paradigm to reveal competition and some of its subtle characteristics in human languages and beyond

Subjective confidence influences word learning in a cross-situational statistical learning task

International audienceLearning is often accompanied by a subjective sense of confidence in one’s knowledge, a feeling of knowing what you know and how well you know it. Subjective confidence has been shown to guide learning in other domains, but has received little attention so far in the word learning literature. Across three word learning experiments, we investigated whether and how a sense of confidence in having acquired a word meaning influences the word learning process itself. First, we show evidence for a confirmation bias during word learning in a cross-situational statistical learning task: Learners who are highly confident they know the meaning of a word are more likely to persist in their belief than learners who are not, even after observing objective evidence disconfirming their belief. Second, we show that subjective confidence in a word meaning modulates inferential processes based on that word, affecting learning over the whole lexicon: Learners who hold high confidence in a word meaning are more likely to use that word to make mutual exclusivity inferences about the meaning of other words. We conclude that confidence influences word learning by modulating both information selection processes and inferential processes and discuss the implications of these results for word learning models

Words cluster phonetically beyond phonotactic regularities

Recent evidence suggests that cognitive pressures associated with language acquisition and use could affect the organization of the lexicon. On one hand, consistent with noisy channel models of language (e.g., Levy, 2008), the phonological distance between wordforms should be maximized to avoid perceptual confusability (a pressure for dispersion). On the other hand, a lexicon with high phonological regularity would be simpler to learn, remember and produce (e.g., Monaghan et al., 2011) (a pressure for clumpiness). Here we investigate wordform similarity in the lexicon, using measures of word distance (e.g., phonological neighborhood density) to ask whether there is evidence for dispersion or clumpiness of wordforms in the lexicon. We develop a novel method to compare lexicons to phonotactically-controlled baselines that provide a null hypothesis for how clumpy or sparse wordforms would be as the result of only phonotactics. Results for four languages, Dutch, English, German and French, show that the space of monomorphemic wordforms is clumpier than what would be expected by the best chance model according to a wide variety of measures: minimal pairs, average Levenshtein distance and several network properties. This suggests a fundamental drive for regularity in the lexicon that conflicts with the pressure for words to be as phonologically distinct as possible. Keywords: Linguistics; Lexical design; Communication; Phonotactic

Coordination, rather than pragmatics, shapes colexification when the pressure forefficiency is low.

We investigate the phenomenon of colexification, where a single word form is associated with multiple meanings. Previous research on colexification has primarily focused on empirical studies of different properties of the meanings that determine colexification, such as semantic similarity or meaning frequency. Meanwhile, little attention was paid to the word-forms’ properties, despite being the original approach advocated by Zipf. Our preregistered study examines whether word length influences word choice for colexification using a noveldyadic communication game (N = 64) and a computational model grounded in the Rational Speech Act (RSA) framework.Contrary to initial predictions, participants did not exhibit a strong preference for efficient colexification (namely colexifying multiple concepts using short words, when long alternatives are available). The results align more closely with a simpler coordination model, where dyads align on a functioning lexical convention with relatively little influence from the efficiency of that convention. Our study highlights the possibility that colexification choices are strongly determined by the pressure for coordination, with weaker influences from semantic similarity or meaning frequency. This is most likely explained by weak pressure for efficiency in our experimental design