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Abstract Web-scale discovery service is one of the primary trends in academic libraries. In this research, using referral data, we explore the main referring domains of DOIs, and evaluate the impact of web-scale discovery services on scholarly content seeking. The results show that web-scale discovery services play an important role in directing users to scholarly contents. ProQuest is found to be ranked the first among all the major referring domains. In addition, the time series analysis shows a significant growing trend of ProQuest as a referring service from 2011 to 2016. The monthly trends demonstrate seasonal fluctuations and daily periodicity of referral data. Specifically, there are two low ebbs throughout a year, corresponding to the Summer and Winter vacations. The lowest point in a week is found to be on Saturdays, while the peak normally occurs on Mondays or Tuesdays. [ABSTRACT FROM AUTHOR]

Context: The role of paternal alcohol consumption on fetal and infant health outcomes, and on social facilitation of maternal alcohol consumption during pregnancy, has not been well established. This review identifies the range of impacts of paternal preconception alcohol consumption and alcohol consumption during partner's pregnancy, on maternal consumption, and fetal and infant health outcomes.Evidence Acquisition: The review accessed articles from the following databases: Scopus, Science Direct, Wiley Online, MEDLINE, ProQuest Central, PsycINFO, and Web of Science. The review included medium- and large-scale studies that provided separate paternal alcohol results, had a non-respondent rate ≤20%, an attrition rate ≤10% per year of data collection up to 30%, and were published between 1990 and 2014. The review included both randomly and non-randomly selected studies, and both case-control and non-case-control studies with notation on risk of bias.Evidence Synthesis: Independent extraction and assessment of articles by two authors was conducted using predefined data fields, including study quality indicators, during 2015. Studies included in the review (11 studies, N=41,062) provide evidence that paternal alcohol consumption during preconception or during pregnancy has an impact on maternal health and alcohol consumption during pregnancy, fetal outcomes, and infant health outcomes.Conclusions: Attention to paternal preconception health care related to alcohol consumption is an important future focus in policies dealing with reproductive, prenatal, fetal, and infant health. [ABSTRACT FROM AUTHOR]

Search in audio archives is a challenging problem. Using prosodic information to help find relevant content has been proposed as a complement to word-based retrieval, but its utility has been an open question. We propose a new way to use prosodic information in search, based on a vector-space model, where each point in time maps to a point in a vector space whose dimensions are derived from numerous prosodic features of the local context. Point pairs that are close in this vector space are frequently similar, not only in terms of the dialog activities, but also in topic. Using proximity in this space as an indicator of similarity, we built support for a query-by-example function. Searchers were happy to use this function, and it provided value on a large testset. Prosody-based retrieval did not perform as well as word-based retrieval, but the two sources of information were often non-redundant and in combination they sometimes performed better than either separately. [ABSTRACT FROM AUTHOR]

Abstract: How is it that, given our diverse sensors that are moving at any moment, we get to the idea that there is a more or less permanent world around us that contains objects and living beings and that is endowed with spatial and temporal properties? This question is difficult, it is “the child’s construction of reality” issue. Given the complexity of the underlying phenomena, it requires a dialog between engineering sciences and life sciences to be solved. In this paper, we introduce the contributions to this dialog that have been collected in this special issue. [Copyright &y& Elsevier]

Highlights: [•] It is possible to model affect using a corpus that was collected from an evaluation that was originally meant for non-emotion related assessment. [•] Conversational features could be used as a single source to model user affect in a limited-task domestic agent. [•] Affect could be inferred by directly predicting user satisfaction (modelling satisfaction). [•] User bias is empirically detected within a laboratory-led evaluation in this paper. [•] The effects of Contextual Turns on user satisfaction depend on user skill. [Copyright &y& Elsevier]

Abstract: The purpose of this research was to gain insights into SMS communication among French-speaking adolescents. We analyzed the effects of the writers’ characteristics (age, gender, and SMS-messaging experience) on message length (number of characters and number of words), dialogue structure (with or without an opening and a closing), and message function (informative vs. relational). The SMS messages were produced in a real-world situation. We found differences across writers’ characteristics for all the dependant variables. The commonly reported distinctions between girls and boys were mitigated. Moreover, for dialogical structure, the messages differed from those found in traditional oral and written interactions since 73% of them did not have the conventional opening–message–closing format (the opening and/or the closing was missing). The results are discussed in terms of the specific characteristics that define the SMS register, and potentially relevant approaches to be taken in future research are addressed. [Copyright &y& Elsevier]

Abstract: Current development platforms for designing spoken dialog services feature different kinds of strategies to help designers build, test, and deploy their applications. In general, these platforms are made up of several assistants that handle the different design stages (e.g. definition of the dialog flow, prompt and grammar definition, database connection, or to debug and test the running of the application). In spite of all the advances in this area, in general the process of designing spoken-based dialog services is a time consuming task that needs to be accelerated. In this paper we describe a complete development platform that reduces the design time by using different types of acceleration strategies based on using information from the data model structure and database contents, as well as cumulative information obtained throughout the successive steps in the design. Thanks to these accelerations, the interaction with the platform is simplified and the design is reduced, in most cases, to simple confirmations to the “proposals” that the platform automatically provides at each stage. Different kinds of proposals are available to complete the application flow such as the possibility of selecting which information slots should be requested to the user together, predefined templates for common dialogs, the most probable actions that make up each state defined in the flow, different solutions to solve specific speech-modality problems such as the presentation of the lists of retrieved results after querying the backend database. The platform also includes accelerations for creating speech grammars and prompts, and the SQL queries for accessing the database at runtime. Finally, we will describe the setup and results obtained in a simultaneous summative, subjective and objective evaluations with different designers used to test the usability of the proposed accelerations as well as their contribution to reducing the design time and interaction. [Copyright &y& Elsevier]

Abstract: The present study set out to identify and examine dialogic educational interactions in Finnish pre-school classrooms. Video recordings of five observed pre-school classrooms that had shown a high or moderate quality of instructional support in literacy, maths and science studies were transcribed for micro-scale qualitative content analysis. Three patterns of teacher–child interaction emerged: first, a pattern characterised by the teacher making it possible for the children to demonstrate their knowledge and competence; second, a pattern characterised by the teacher supporting the children''s participation and diverse contributions; and third, a pattern characterised by the teacher allowing dialogical space for a child-initiated sharing of ideas. The findings provide guidelines for professional development programmes seeking to increase teachers’ awareness of ways to support children''s active participation. [Copyright &y& Elsevier]

This paper proposes a generic dialog modeling framework for a multi-domain dialog system to simultaneously manage goal-oriented and chat dialogs for both information access and entertainment. We developed a dialog modeling technique using an example-based approach to implement multiple applications such as car navigation, weather information, TV program guidance, and chatbot. Example-based dialog modeling (EBDM) is a simple and effective method for prototyping and deploying of various dialog systems. This paper also introduces the system architecture of multi-domain dialog systems using the EBDM framework and the domain spotting technique. In our experiments, we evaluate our system using both simulated and real users. We expect that our approach can support flexible management of multi-domain dialogs on the same framework. [Copyright &y& Elsevier]

User simulations are increasingly employed in the development and evaluation of spoken dialog systems. However, there is no accepted method for evaluating user simulations, which is problematic because the performance of new dialog management techniques is often evaluated on user simulations alone, not on real people. In this paper, we propose a novel method of evaluating user simulations. We view a user simulation as a predictor of the performance of a dialog system, where per-dialog performance is measured with a domain-specific scoring function. The divergence between the distribution of dialog scores in the real and simulated corpora provides a measure of the quality of the user simulation, and we argue that the Cramér–von Mises divergence is well-suited to this task. To demonstrate this technique, we study a corpus of callers with real information needs and show that Cramér-von Mises divergence conforms to expectations. Finally, we present simple tools which enable practitioners to interpret the statistical significance of comparisons between user simulations. [Copyright &y& Elsevier]

Spoken dialogue systems must inevitably deal with out-of-grammar utterances. We address this problem in multi-domain spoken dialogue systems, which deal with more tasks than a single-domain system. We defined a topic by augmenting a domain about which users want to find more information, and we developed a method of recovering out-of-grammar utterances based on topic estimation, i.e., by providing a help message in the estimated domain. Moreover, domain extensibility, that is, the ability to add new domains to the system, should be inherently retained in multi-domain systems. To estimate domains without sacrificing extensibility, we collected documents from the Web as training data. Since the data contained a certain amount of noise, we used latent semantic mapping (LSM), which enables robust topic estimation by removing the effects of noise from the data. Experimental results showed that our method improved topic estimation accuracy by 23.2 points for data including out-of-grammar utterances. [Copyright &y& Elsevier]

In this paper, we present a statistical approach for the development of a dialog manager and for learning optimal dialog strategies. This methodology is based on a classification procedure that considers all of the previous history of the dialog to select the next system answer. To evaluate the performance of the dialog system, the statistical approach for dialog management has been extended to model the user behavior. The statistical user simulator has been used for the evaluation and improvement of the dialog strategy. Both the user model and the system model are automatically learned from a training corpus that is labeled in terms of dialog acts. New measures have been defined to evaluate the performance of the dialog system. Using these measures, we evaluate both the quality of the simulated dialogs and the improvement of the new dialog strategy that is obtained with the interaction of the two modules. This methodology has been applied to develop a dialog manager within the framework of the DIHANA project, whose goal is the design and development of a dialog system to access a railway information system using spontaneous speech in Spanish. We propose the use of corpus-based methodologies to develop the main modules in the dialog system. [Copyright &y& Elsevier]

Summary: Objective: The objective of this research was to build an intelligent tutoring system capable of carrying on a natural language dialogue with a student who is solving a problem in physiology. Previous experiments have shown that students need practice in qualitative causal reasoning to internalize new knowledge and to apply it effectively and that they learn by putting their ideas into words. Methods: Analysis of a corpus of 75 hour-long tutoring sessions carried on in keyboard-to-keyboard style by two professors of physiology at Rush Medical College tutoring first-year medical students provided the rules used in tutoring strategies and tactics, parsing, and text generation. The system presents the student with a perturbation to the blood pressure, asks for qualitative predictions of the changes produced in seven important cardiovascular variables, and then launches a dialogue to correct any errors and to probe for possible misconceptions. The natural language understanding component uses a cascade of finite-state machines. The generation is based on lexical functional grammar. Results: Results of experiments with pretests and posttests have shown that using the system for an hour produces significant learning gains and also that even this brief use improves the student''s ability to solve problems more then reading textual material on the topic. Student surveys tell us that students like the system and feel that they learn from it. The system is now in regular use in the first-year physiology course at Rush Medical College. Conclusion: We conclude that the CIRCSIM–Tutor system demonstrates that intelligent tutoring systems can implement effective natural language dialogue with current language technology. [Copyright &y& Elsevier]