The Sheffield Search and Rescue corpus

© 2017 IEEE. As part of an ongoing research into extracting mission-critical information from Search and Rescue speech communications, a corpus of unscripted, goal-oriented, two-party spoken conversations has been designed and collected. The Sheffield Search and Rescue (SSAR) corpus comprises about 12 hours of data from 96 conversations by 24 native speakers of British English with a southern accent. Each conversation is about a collaborative task of exploring and estimating a simulated indoor environment. The task has carefully been designed to have a quantitative measure for the amount of exchanged information about the discourse subject. SSAR includes different layers of annotations which should be of interest to researchers in a wide range of human/human conversation understanding as well as automatic speech recognition. It also provides an amount of data for analysis of multiple parallel conversations around a single subject. The SSAR corpus is available for research purposes

Stepping back from crisis points : the provision and acknowledgement of support in an online suicide discussion forum

Suicide is a global health concern, though little is known about the social practices that might support those who are contemplating suicide. Online forums provide a unique insight into the anonymous discussion of suicide, including sociocultural norms about suicide and the delicate management of online interaction. This article examines the provision and acknowledgement of support in an online discussion forum about suicide, using discursive psychology to analyse the textual interaction. The analysis illustrates how forum threads function as case studies, and enable members to gain support on numerous occasions. In this way, members can gain help at crisis points as and when these occur, while still maintaining authenticity as a valid forum member. The analysis also provides additional evidence for models of suicide which highlight the fluid nature of suicidality and contributes to the preventative work on suicide by demonstrating how support can be provided at crisis points. 2 Suicidal behaviours represent a global public health concern and substantial research effort has gone into identifying specific risk and protective factors (e.g., O'Connor & Nock, 2014) . The rise of technology provides a unique opportunity to examine suicidal issues in online spaces (Mishara & Kerkhof, 2013) , yet research to date has focused mainly on the motivations and individual characteristics of those using the internet for this purpose, rather than on the social practices in the online spaces themselves. Following Horne and Wiggins (2009) and Paulus and Varga (2015), this article focuses on the provision and acknowledgement of support in an o nline suicide di scussion forum. Specifically, the aim of this article is to explicate the interactional features of support in the suicide forums, and of the potential for members to be supported by others by being metaphorically talked back from the ‘edge’; i.e., representing a shift from being at a crisis point to a stance that might still be troubled but is not immediately suicidal. As such, the article provides additional empirical support for discursive accounts of managing health identities online as well as demonstrating the potential of qualitative analyses to contribute to preventative work on suicid

Deriving and Exploiting Situational Information in Speech: Investigations in a Simulated Search and Rescue Scenario

The need for automatic recognition and understanding of speech is emerging in tasks involving the processing of large volumes of natural conversations. In application domains such as Search and Rescue, exploiting automated systems for extracting mission-critical information from speech communications has the potential to make a real difference. Spoken language understanding has commonly been approached by identifying units of meaning (such as sentences, named entities, and dialogue acts) for providing a basis for further discourse analysis. However, this fine-grained identification of fundamental units of meaning is sensitive to high error rates in the automatic transcription of noisy speech. This thesis demonstrates that topic segmentation and identification techniques can be employed for information extraction from spoken conversations by being robust to such errors. Two novel topic-based approaches are presented for extracting situational information within the search and rescue context. The first approach shows that identifying the changes in the context and content of first responders' report over time can provide an estimation of their location. The second approach presents a speech-based topological map estimation technique that is inspired, in part, by automatic mapping algorithms commonly used in robotics. The proposed approaches are evaluated on a goal-oriented conversational speech corpus, which has been designed and collected based on an abstract communication model between a first responder and a task leader during a search process. Results have confirmed that a highly imperfect transcription of noisy speech has limited impact on the information extraction performance compared with that obtained on the transcription of clean speech data. This thesis also shows that speech recognition accuracy can benefit from rescoring its initial transcription hypotheses based on the derived high-level location information. A new two-pass speech decoding architecture is presented. In this architecture, the location estimation from a first decoding pass is used to dynamically adapt a general language model which is used for rescoring the initial recognition hypotheses. This decoding strategy has resulted in a statistically significant gain in the recognition accuracy of the spoken conversations in high background noise. It is concluded that the techniques developed in this thesis can be extended to more application domains that deal with large volumes of natural spoken conversations

A social media and crowd-sourcing data mining system for crime prevention during and post-crisis situations

A number of large crisis situations, such as natural disasters have affected the planet over the last decade. The outcomes of such disasters are catastrophic for the infrastructures of modern societies. Furthermore, after large disasters, societies come face-to-face with important issues, such as the loss of human lives, people who are missing and the increment of the criminality rate. In many occasions, they seem unprepared to face such issues. This paper aims to present an automated system for the synchronization of the police and Law Enforcement Agencies (LEAs) for the prevention of criminal activities during and post a large crisis situation. The paper presents a review of the literature focusing on the necessity of using data mining in combination with advanced web technologies, such as social media and crowd-sourcing, for the resolution of the problems related to criminal activities caused during and post-crisis situations. The paper provides an introduction to examples of different techniques and algorithms used for social media and crowd-sourcing scanning, such as sentiment analysis and link analysis. The main focus of the paper is the ATHENA Crisis Management system. The function of the ATHENA system is based on the use of social media and crowd-sourcing for collecting crisis-related information. The system uses a number of data mining techniques to collect and analyze data from the social media for the purpose of crime prevention. A number of conclusions are drawn on the significance of social media and crowd-sourcing data mining techniques for the resolution of problems related to large crisis situations with emphasis to the ATHENA system

Off-record politeness in Sophocles: The patterned dialogues of female characters

This paper tests the applicability of Brown and Levinson’s concept of off-record politeness on a specific sub-set of patterned dialogues in Sophocles’ extant tragedies, i.e., those involving the participation of female speakers. Brown and Levinson’s framework still provides the most suitable model for empirical analysis, but with refinements concerning the interrelation between emic and etic politeness, the notion of face, the extension of analysis to longer stretches of conversation, and the absolute ranking of the super-strategies. The survey suggests that a strict connection between the use of off record and the mitigation of FTAs can be established quite straightforwardly and that the hearer’s reactions to off record can help to identify the valid instances of the phenomenon. Moreover, it is argued that (a) female speakers frequently resort to off record, most notably in cross-sex interactions with men invested with high power; (b) few restricted categories of male speakers, i.e., strangers and lower-status characters, do use off-record politeness towards women; (c) off record in same-sex interactions among female characters is limited to when the imposition is of extraordinary seriousness

Explicit diversification of event aspects for temporal summarization

During major events, such as emergencies and disasters, a large volume of information is reported on newswire and social media platforms. Temporal summarization (TS) approaches are used to automatically produce concise overviews of such events by extracting text snippets from related articles over time. Current TS approaches rely on a combination of event relevance and textual novelty for snippet selection. However, for events that span multiple days, textual novelty is often a poor criterion for selecting snippets, since many snippets are textually unique but are semantically redundant or non-informative. In this article, we propose a framework for the diversification of snippets using explicit event aspects, building on recent works in search result diversification. In particular, we first propose two techniques to identify explicit aspects that a user might want to see covered in a summary for different types of event. We then extend a state-of-the-art explicit diversification framework to maximize the coverage of these aspects when selecting summary snippets for unseen events. Through experimentation over the TREC TS 2013, 2014, and 2015 datasets, we show that explicit diversification for temporal summarization significantly outperforms classical novelty-based diversification, as the use of explicit event aspects reduces the amount of redundant and off-topic snippets returned, while also increasing summary timeliness

The Renewal of Song: Metalepsis and the Christological Revision of Psalmody in Paul

The productive yield of Richard Hays’ Echoes of Scripture in the Letters of Paul for the study of Pauline intertextuality has not been matched by adequate reflection on questions of method, particularly on the character of the trope at the heart of the Haysian project: metalepsis, or “echo”. Nor has sufficient attention been given to the reception of biblical psalmody in Paul, and to the distinctiveness of psalmic discourse in relation to metaleptic process. This study accordingly attempts a close engagement with biblical psalmody as this appears at selected sites in Romans and 2 Corinthians, focusing on those sites which best demonstrate the distinctive character of psalmody, and so offer to refine an account of metalepsis. In particular, it examines quotations which are attributed or attributable to David or to Christ, and sites in which psalmody serves to modulate Paul’s discourse without recourse to quotation. In so doing, this study sets out to enrich the Haysian account of metalepsis by discerning and correcting two biases. In relation to method, Haysian metalepsis is found to license maximalist readings of intertexts on the presumption of narrativity, which cannot be fully sustained in relation to psalmody. In relation to hermeneutics, Haysian metalepsis is shown to privilege dialectical accounts of Pauline intertextuality, in which the voice of scripture is richly and sympathetically invoked in Paul’s discourse. By resisting these biases, the present study is able to offer a more nuanced account of metalepsis, one better suited to psalmody, and to discern a more complex picture of Pauline intertextuality. Within it, Christ is richly configured as a psalmist in Paul, rhetorically empowered and tendered for imitation, yet nearly always at the expense of David, subverting the mode of agency he represents, in hermeneutical gestures which are dialectical in form but heuristic in effect

Constructed Languages and Their Role in Drama

This paper covers the history and use of constructed language and dialect on stage and screen as well as the issues that arise concerning social awareness and intellectual property

Mapping Austerity: Geographical Text Analysis of UK Place-Names in <i>The Guardian</i> and <i>The Daily Telegraph</i>

By analysing corpora of newspaper articles from The Guardian and The Daily Telegraph this chapter uses a modified form of geographical text analysis (GTA) to investigate whether (and in what form) mass media texts express a relationship between austerity and UK places. Concordance geoparsing is used to detect the use of place-names occurring within a set span of key terms, such as austerity, policy, crisis, measures and spending. The geoparsing process generates Place-Name Co-occurrences (PNCs), which are comprised of a search term, a place-name, its coordinates, and its surrounding co-text. The coordinates of PNCs can be plotted on maps using GIS (Geographical Information Systems) software, to show patterns in place-name mentions, while the co-text is well-suited to linguistic analysis. Ultimately, GTA facilitates the visualisation of corpora and adds the consideration of physical space to language analysis. The results of GTA show that coverage of UK austerity focuses overwhelmingly on England and that both newspapers are London-centric