Generating text descriptions for geographically distributed sensors

Sensor networks, with thousands of geographically distributed sensors and different types of quantitative measures, need software tools to help users understand the meaning of measures. In this paper we pay attention to the problem of automatic generation of geographic descriptions in natural language for geographically distributed sensors. We describe this problem in the context of a web application in the domain of hydrology which is part of a more complex multimedia presentation system that combines text and graphics. We describe the web application and the algorithm that we designed to generate the geographic descriptions for sensors. Besides GIS data files, our method uses two information sources: an online server for geographic names (Geonames) and a specific knowledge base with text patterns that we constructed to process sensor identifiers. The evaluation results confirm that online geographic information resources such as Geonames are useful to generate names for sensors but they need to be combined with other more specific information sources (such as our knowledge base) to obtain good descriptions. We also compare our method with related work and show future lines of work

Talking about Relations:Factors Influencing the Production of Relational Descriptions

In a production experiment (Experiment 1) and an acceptability rating one (Experiment 2), we assessed two factors, spatial position and salience, which may influence the production of relational descriptions (such as the ball between the man and the drawer). In Experiment 1, speakers were asked to refer unambiguously to a target object (a ball). In Experiment 1a, we addressed the role of spatial position, more specifically if speakers mention the entity positioned leftmost in the scene as (first) relatum. The results showed a preference to start with the left entity, however, only as a trend, which leaves room for other factors that could influence spatial reference. Thus, in the following studies, we varied salience systematically, by making one of the relatum candidates animate (Experiment 1b), and by adding attention capture cues, first subliminally by priming one relatum candidate with a flash (Experiment 1c), then explicitly by using salient colors for objects (Experiment 1d). Results indicate that spatial position played a dominant role. Entities on the left were mentioned more often as (first) relatum than those on the right (Experiment 1a, 1b, 1c, 1d). Animacy affected reference production in one out of three studies (in Experiment 1d). When salience was manipulated by priming visual attention or by using salient colors, there were no significant effects (Experiment 1c, 1d). In the acceptability rating study (Experiment 2), participants expressed their preference for specific relata, by ranking descriptions on the basis of how good they thought the descriptions fitted the scene. Results show that participants preferred most the description that had an animate entity as the first mentioned relatum. The relevance of these results for models of reference production is discussed

FOUND IN SPACE: A CROSS-LINGUISTIC ANALYSIS OF SECOND LANGUAGE LEARNERS IN ENGLISH MAP TASK PERFORMANCE

Understanding the relationship between first and second language use in the area of spatial language has broader implications for our understanding of language learning and consequences for the construction of bilingual assessment instruments for second language learners. This study shows that observing and interpreting the task of map drawing and the related behavior of explaining maps can be a way to explore the linguistic emergence of the conceptualization of spatial language (at a moment of simultaneous and synchronized incarnation). Altogether, 50 dyads (pairs) participated in the New Mexico Map Task Project; the project included native speakers of English, Russian, Japanese, Navajo, and Spanish. In an examination of how the grammatical constructions used for spatial descriptions in a speaker\u27s first language carry over into the usage of this speaker\u27s second language, new observations include the intra-subject comparison of dyadic map task performances. Each non-native English-speaking dyad participates in two map task performances: one in their native language and one in their second language, English. Evidence was generated through morphosyntactic, phonological, and pragmatic analyses performed on the sound files of the transcripts. This evidence confirms the connection between the participants\u27 productions of tokens of selected landmark names both in their native language and their second language. Combining the results of linguistic analyses with educational assessment frameworks predicts the development of an instrument for use with immigrant and refugee students from areas of conflict