Conceptualization in reference production:Probabilistic modeling and experimental testing

In psycholinguistics, there has been relatively little work investigating conceptualization-how speakers decide which concepts to express. This contrasts with work in natural language generation (NLG), a subfield of artificial intelligence, where much research has explored content determination during the generation of referring expressions. Existing NLG algorithms for conceptualization during reference production do not fully explain previous psycholinguistic results, so we developed new models that we tested in three language production experiments. In our experiments, participants described target objects to another participant. In Experiment 1, either size, color, or both distinguished the target from all distractor objects; in Experiment 2, either color, type, or both color and type distinguished it from all distractors; In Experiment 3, color, size, or the border around the object distinguished the target. We tested how well the different models fit the distribution of description types (e.g., "small candle," "gray candle," "small gray candle") that participants produced. Across these experiments, the probabilistic referential overspecification model (PRO) provided the best fit. In this model, speakers first choose a property that rules out all distractors. If there is more than one such property, then they probabilistically choose one on the basis of a preference for that property. Next, they sometimes add another property, with the probability again determined by its preference and speakers' eagerness to overspecify

Differences in Internet use and eHealth needs of adolescent and young adult versus older cancer patients:Results from the PROFILES registry

SIMPLE SUMMARY: The internet has become an important health information source for patients with cancer. AYAs (adolescents and young adults; 18–39 years at time of diagnosis) can be considered as digital natives; they work with the internet and related technologies in their daily lives. It is likely that AYAs are more used to using the internet, while older cancer patients might prefer former ways of information provision to obtain health-related information. The question arises whether internet use and eHealth needs of AYA cancer patients are comparable to those of older ones. By conducting a cross-sectional survey, we evaluated differences in cancer-related internet patterns between AYAs and older cancer patients (40+ years at time of diagnosis). A better understanding of differences between generations will help inform healthcare providers on how to guide cancer patients of different ages regarding cancer-related internet use. ABSTRACT: Background: Our aim was to evaluate differences in cancer-related internet patterns between AYAs (adolescents and young adults; 18–39 years at time of diagnosis) and older adult cancer patients (40+ years). Methods: Cross-sectional surveys were distributed among AYA and older adult cancer patients regarding cancer-related internet use and eHealth needs. Results: 299 AYAs (mean age 31.8 years) and 270 older adults (mean age 55.8 years) participated. AYAs searched significantly more often on the internet on a daily basis just before diagnosis (45% vs. 37%), right after diagnosis (71% vs. 62%) and during treatment (65% vs. 59%) compared to older adults. During follow up, there was a trend that AYAs searched less often on the internet compared to older adults (15% vs. 17%). AYAs searched more often on topics, such as alternative or complementary therapies, treatment guidelines, fertility, end of life, sexuality and intimacy, lifestyle and insurance. AYAs felt significantly better informed (75%) after searching for cancer-related information compared to older adults (65%) and had significantly less unmet needs regarding access to their own medical information (22% vs. 47%). AYAs search more on the internet on a daily basis/several times per week in the diagnosis and treatment phase than older cancer patients. They search on different topics than older adults and seems to have less unmet eHealth needs.It is important that these are easy to find and reliable

A toy or a friend? Children's anthropomorphic beliefs about robots and how these relate to second-language word learning

This study investigates the degree to which children anthropomorphize a robot tutor and whether this anthropomorphism relates to their vocabulary learning in a second-language (L2) tutoring intervention. With this aim, an anthropomorphism questionnaire was administered to 5-year-old children (N = 104) twice: prior to and following a seven-session L2 vocabulary training with a humanoid robot. On average, children tended to anthropomorphize the robot prior to and after the lessons to a similar degree, but many children changed their attributed anthropomorphic features. Boys anthropomorphized the robot less after the lessons than girls. Moreover, there was a weak but significant positive correlation between anthropomorphism as measured before the lessons and scores on a word-knowledge post-test administered the day after the last lesson. There was also a weak but significant positive correlation between the change in anthropomorphism over time and scores on a word-knowledge post-test administered approximately 2 weeks after the last lesson. Our results underscore the need to manage children's expectations in robot-assisted education. Also, future research could explore adaptations to individual children's expectations in child-robot interactions

Guidelines for Designing Social Robots as Second Language Tutors

In recent years, it has been suggested that social robots have potential as tutors and educators for both children and adults. While robots have been shown to be effective in teaching knowledge and skill-based topics, we wish to explore how social robots can be used to tutor a second language to young children. As language learning relies on situated, grounded and social learning, in which interaction and repeated practice are central, social robots hold promise as educational tools for supporting second language learning. This paper surveys the developmental psychology of second language learning and suggests an agenda to study how core concepts of second language learning can be taught by a social robot. It suggests guidelines for designing robot tutors based on observations of second language learning in human–human scenarios, various technical aspects and early studies regarding the effectiveness of social robots as second language tutors

Multidimensional signals and analytic flexibility: Estimating degrees of freedom in human speech analyses

Recent empirical studies have highlighted the large degree of analytic flexibility in data analysis which can lead to substantially different conclusions based on the same data set. Thus, researchers have expressed their concerns that these researcher degrees of freedom might facilitate bias and can lead to claims that do not stand the test of time. Even greater flexibility is to be expected in fields in which the primary data lend themselves to a variety of possible operationalizations. The multidimensional, temporally extended nature of speech constitutes an ideal testing ground for assessing the variability in analytic approaches, which derives not only from aspects of statistical modeling, but also from decisions regarding the quantification of the measured behavior. In the present study, we gave the same speech production data set to 46 teams of researchers and asked them to answer the same research question, resulting insubstantial variability in reported effect sizes and their interpretation. Using Bayesian meta-analytic tools, we further find little to no evidence that the observed variability can be explained by analysts’ prior beliefs, expertise or the perceived quality of their analyses. In light of this idiosyncratic variability, we recommend that researchers more transparently share details of their analysis, strengthen the link between theoretical construct and quantitative system and calibrate their (un)certainty in their conclusions

A partial account of presupposition projection

In this paper it is shown how a partial semantics for presuppositions can be given which is empirically more satisfactory than its predecessors, and how this semantics can be integrated with a technically sound, compositional grammar in the Montagovian fashion. Additionally, it is argued that the classical objection to partial accounts of presupposition projection, namely that they lack flexibility, is based on a misconception. Partial logics can give rise to flexible predictions without postulating any ad hoc ambiguities. Finally, it is shown how the partial foundation can be combined with a dynamic system of common-ground maintenance to account for accommodation

How Do Friends and Strangers Play the Game Taboo? A Study of Accuracy, Efficiency, Motivation, and the Use of Shared Knowledge

According to common belief, friends communicate more accurately and efficiently than strangers, because they can use uniquely shared knowledge and common knowledge to explain things to each other, while strangers are restricted to common knowledge. To test this belief, we asked friends and strangers to play, via e-mail and face-to-face, the word-description game Taboo, in which objects need to be described without using certain “taboo” words. When descriptions were sent via e-mail, there was no difference in accuracy (number of correct answers) nor in efficiency (number of words per correct answer) between friends and strangers. When descriptions were given face-to-face, friends were more accurate than strangers, but not more efficient (number of seconds and words per correct answer). Shared knowledge did not predict accuracy or efficiency. Hence, our findings do not support the idea that friends only need a few words to understand each other