19 research outputs found

    Adapting the NICT-JLE Corpus for Disfluency Detection Models

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    The detection of disfluencies such as hesitations, repetitions and false starts commonly found in speech is a widely studied area of research. With a standardised process for evaluation using the Switchboard Corpus, model performance can be easily compared across approaches. This is not the case for disfluency detection research on learner speech, however, where such datasets have restricted access policies, making comparison and subsequent development of improved models more challenging. To address this issue, this paper describes the adaptation of the NICT-JLE corpus, containing approximately 300 hours of English learners' oral proficiency tests, to a format that is suitable for disfluency detection model training and evaluation. Points of difference between the NICT-JLE and Switchboard corpora are explored, followed by a detailed overview of adaptations to the tag set and meta-features of the NICT-JLE corpus. The result of this work provides a standardised train, heldout and test set for use in future research on disfluency detection for learner speech

    Incremental Disfluency Detection for Spoken Learner English

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    Dialogue-based computer-assisted language learning (CALL) concerns the application and analysis of automated systems that engage with a language learner through dialogue. Routed in an interactionist perspective of second language acquisition, dialogue-based CALL systems assume the role of a speaking partner, providing learners the opportunity for spontaneous production of their second language. One area of interest for such systems is the implementation of corrective feedback. However, the feedback strategies employed by such systems remain fairly limited. In particular, there are currently no provisions for learners to initiate the correction of their own errors, despite this being the most frequently occurring and most preferred type of error correction in learner speech. To address this gap, this thesis proposes a framework for implementing such functionality, identifying incremental self-initiated self-repair (i.e. disfluency) detection as a key area for research. Taking an interdisciplinary approach to the exploration of this topic, this thesis outlines the steps taken to optimise an incremental disfluency detection model for use with spoken learner English. To begin, a linguistic comparative analysis of native and learner disfluency corpora explored the differences between the disfluency behaviour of native and learner speech, highlighting key features of learner speech not previously explored in disfluency detection model analysis. Following this, in order to identify a suitable baseline model for further experimentation, two state-of-the-art incremental self-repair detection models were trained and tested with a learner speech corpus. An error analysis of the models' outputs found an LSTM model using word embeddings and part-of-speech tags to be the most suitable for learner speech, thanks to its lower number of false positives triggered by learner errors in the corpus. Following this, several adaptations to the model were tested to improve performance. Namely, the inclusion of character embeddings, silence and laughter features, separating edit term detection from disfluency detection, lemmatization and the inclusion of learners' prior proficiency scores led to over an eight percent model improvement over the baseline. Findings from this thesis illustrate how the analysis of language characteristics specific to learner speech can positively inform model adaptation and provide a starting point for further investigation into the implementation of effective corrective feedback strategies in dialogue-based CALL systems

    Building essential biodiversity variables (EBVs) of species distribution and abundance at a global scale

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    Much biodiversity data is collected worldwide, but it remains challenging to assemble the scattered knowledge for assessing biodiversity status and trends. The concept of Essential Biodiversity Variables (EBVs) was introduced to structure biodiversity monitoring globally, and to harmonize and standardize biodiversity data from disparate sources to capture a minimum set of critical variables required to study, report and manage biodiversity change. Here, we assess the challenges of a 'Big Data' approach to building global EBV data products across taxa and spatiotemporal scales, focusing on species distribution and abundance. The majority of currently available data on species distributions derives from incidentally reported observations or from surveys where presence-only or presence-absence data are sampled repeatedly with standardized protocols. Most abundance data come from opportunistic population counts or from population time series using standardized protocols (e.g. repeated surveys of the same population from single or multiple sites). Enormous complexity exists in integrating these heterogeneous, multi-source data sets across space, time, taxa and different sampling methods. Integration of such data into global EBV data products requires correcting biases introduced by imperfect detection and varying sampling effort, dealing with different spatial resolution and extents, harmonizing measurement units from different data sources or sampling methods, applying statistical tools and models for spatial inter- or extrapolation, and quantifying sources of uncertainty and errors in data and models. To support the development of EBVs by the Group on Earth Observations Biodiversity Observation Network (GEO BON), we identify 11 key workflow steps that will operationalize the process of building EBV data products within and across research infrastructures worldwide. These workflow steps take multiple sequential activities into account, including identification and aggregation of various raw data sources, data quality control, taxonomic name matching and statistical modelling of integrated data. We illustrate these steps with concrete examples from existing citizen science and professional monitoring projects, including eBird, the Tropical Ecology Assessment and Monitoring network, the Living Planet Index and the Baltic Sea zooplankton monitoring. The identified workflow steps are applicable to both terrestrial and aquatic systems and a broad range of spatial, temporal and taxonomic scales. They depend on clear, findable and accessible metadata, and we provide an overview of current data and metadata standards. Several challenges remain to be solved for building global EBV data products: (i) developing tools and models for combining heterogeneous, multi-source data sets and filling data gaps in geographic, temporal and taxonomic coverage, (ii) integrating emerging methods and technologies for data collection such as citizen science, sensor networks, DNA-based techniques and satellite remote sensing, (iii) solving major technical issues related to data product structure, data storage, execution of workflows and the production process/cycle as well as approaching technical interoperability among research infrastructures, (iv) allowing semantic interoperability by developing and adopting standards and tools for capturing consistent data and metadata, and (v) ensuring legal interoperability by endorsing open data or data that are free from restrictions on use, modification and sharing. Addressing these challenges is critical for biodiversity research and for assessing progress towards conservation policy targets and sustainable development goals

    SPARC 2019 Fake news & home truths : Salford postgraduate annual research conference book of abstracts

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    Welcome to the Book of Abstracts for the 2019 SPARC conference. This year we not only celebrate the work of our PGRs but also our first ever Doctoral School Best Supervisor awards, which makes this year’s conference extra special. Once again we have received a tremendous contribution from our postgraduate research community; with over 90 presenters, the conference truly showcases a vibrant, innovative and collaborative PGR community at Salford. These abstracts provide a taster of the inspiring, relevant and impactful research in progress, and provide delegates with a reference point for networking and initiating critical debate. Find an abstract that interests you, and say “Hello” to the author. Who knows what might result from your conversation? With such wide-ranging topics being showcased, we encourage you to take up this great opportunity to engage with researchers working in different subject areas from your own. To meet global challenges, high impact research needs interdisciplinary collaboration. This is recognised and rewarded by all major research funders. Engaging with the work of others and forging collaborations across subject areas is an essential skill for the next generation of researchers. Even better, our free ice cream van means that you can have those conversations while enjoying a refreshing ice lolly

    Alcohol harm reduction legacy document

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    Alcohol harm reduction legacy document

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    Does journal endorsement of reporting guidelines influence the completeness of reporting of health research? A systematic review protocol

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    Background: Reporting of health research is often inadequate and incomplete. Complete and transparent reporting is imperative to enable readers to assess the validity of research findings for use in healthcare and policy decision-making. To this end, many guidelines, aimed at improving the quality of health research reports, have been developed for reporting a variety of research types. Despite efforts, many reporting guidelines are underused. In order to increase their uptake, evidence of their effectiveness is important and will provide authors, peer reviewers and editors with an important resource for use and implementation of pertinent guidance. The objective of this study was to assess whether endorsement of reporting guidelines by journals influences the completeness of reporting of health studies. Methods: Guidelines providing a minimum set of items to guide authors in reporting a specific type of research, developed with explicit methodology, and using a consensus process will be identified from an earlier systematic review and from the EQUATOR (Enhancing the QUAlity and Transparency Of health Research) Network’s reporting guidelines library. MEDLINE, EMBASE, the Cochrane Methodology Register and Scopus will be searched for evaluations of those reporting guidelines; relevant evaluations from the recently conducted CONSORT systematic review will also be included. Single data extraction with 10% verification of study characteristics, 20% of outcomes and complete verification of aspects of study validity will be carried out. We will include evaluations of reporting guidelines that assess the completeness of reporting: (1) before and after journal endorsement, and/or (2) between endorsing and non-endorsing journals. For a given guideline, analyses will be conducted for individual and the total sum of items. When possible, standard, pooled effects with 99% confidence intervals using random effects models will be calculated. Discussion: Evidence on which guidelines have been evaluated and which are associated with improved completeness of reporting is important for various stakeholders, including editors who consider which guidelines to endorse in their journal editorial policies.Other UBCNon UBCReviewedFacult

    Does journal endorsement of reporting guidelines influence the completeness of reporting of health research? A systematic review protocol

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    Abstract Background Reporting of health research is often inadequate and incomplete. Complete and transparent reporting is imperative to enable readers to assess the validity of research findings for use in healthcare and policy decision-making. To this end, many guidelines, aimed at improving the quality of health research reports, have been developed for reporting a variety of research types. Despite efforts, many reporting guidelines are underused. In order to increase their uptake, evidence of their effectiveness is important and will provide authors, peer reviewers and editors with an important resource for use and implementation of pertinent guidance. The objective of this study was to assess whether endorsement of reporting guidelines by journals influences the completeness of reporting of health studies. Methods Guidelines providing a minimum set of items to guide authors in reporting a specific type of research, developed with explicit methodology, and using a consensus process will be identified from an earlier systematic review and from the EQUATOR (Enhancing the QUAlity and Transparency Of health Research) Network’s reporting guidelines library. MEDLINE, EMBASE, the Cochrane Methodology Register and Scopus will be searched for evaluations of those reporting guidelines; relevant evaluations from the recently conducted CONSORT systematic review will also be included. Single data extraction with 10% verification of study characteristics, 20% of outcomes and complete verification of aspects of study validity will be carried out. We will include evaluations of reporting guidelines that assess the completeness of reporting: (1) before and after journal endorsement, and/or (2) between endorsing and non-endorsing journals. For a given guideline, analyses will be conducted for individual and the total sum of items. When possible, standard, pooled effects with 99% confidence intervals using random effects models will be calculated. Discussion Evidence on which guidelines have been evaluated and which are associated with improved completeness of reporting is important for various stakeholders, including editors who consider which guidelines to endorse in their journal editorial policies.</p

    Systematic review adherence to methodological or reporting quality

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    Abstract Background Guidelines for assessing methodological and reporting quality of systematic reviews (SRs) were developed to contribute to implementing evidence-based health care and the reduction of research waste. As SRs assessing a cohort of SRs is becoming more prevalent in the literature and with the increased uptake of SR evidence for decision-making, methodological quality and standard of reporting of SRs is of interest. The objective of this study is to evaluate SR adherence to the Quality of Reporting of Meta-analyses (QUOROM) and PRISMA reporting guidelines and the A Measurement Tool to Assess Systematic Reviews (AMSTAR) and Overview Quality Assessment Questionnaire (OQAQ) quality assessment tools as evaluated in methodological overviews. Methods The Cochrane Library, MEDLINE®, and EMBASE® databases were searched from January 1990 to October 2014. Title and abstract screening and full-text screening were conducted independently by two reviewers. Reports assessing the quality or reporting of a cohort of SRs of interventions using PRISMA, QUOROM, OQAQ, or AMSTAR were included. All results are reported as frequencies and percentages of reports and SRs respectively. Results Of the 20,765 independent records retrieved from electronic searching, 1189 reports were reviewed for eligibility at full text, of which 56 reports (5371 SRs in total) evaluating the PRISMA, QUOROM, AMSTAR, and/or OQAQ tools were included. Notable items include the following: of the SRs using PRISMA, over 85% (1532/1741) provided a rationale for the review and less than 6% (102/1741) provided protocol information. For reports using QUOROM, only 9% (40/449) of SRs provided a trial flow diagram. However, 90% (402/449) described the explicit clinical problem and review rationale in the introduction section. Of reports using AMSTAR, 30% (534/1794) used duplicate study selection and data extraction. Conversely, 80% (1439/1794) of SRs provided study characteristics of included studies. In terms of OQAQ, 37% (499/1367) of the SRs assessed risk of bias (validity) in the included studies, while 80% (1112/1387) reported the criteria for study selection. Conclusions Although reporting guidelines and quality assessment tools exist, reporting and methodological quality of SRs are inconsistent. Mechanisms to improve adherence to established reporting guidelines and methodological assessment tools are needed to improve the quality of SRs

    Identifying approaches for assessing methodological and reporting quality of systematic reviews: a descriptive study

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    Abstract Background The methodological quality and completeness of reporting of the systematic reviews (SRs) is fundamental to optimal implementation of evidence-based health care and the reduction of research waste. Methods exist to appraise SRs yet little is known about how they are used in SRs or where there are potential gaps in research best-practice guidance materials. The aims of this study are to identify reports assessing the methodological quality (MQ) and/or reporting quality (RQ) of a cohort of SRs and to assess their number, general characteristics, and approaches to ‘quality’ assessment over time. Methods The Cochrane Library, MEDLINE®, and EMBASE® were searched from January 1990 to October 16, 2014, for reports assessing MQ and/or RQ of SRs. Title, abstract, and full-text screening of all reports were conducted independently by two reviewers. Reports assessing the MQ and/or RQ of a cohort of ten or more SRs of interventions were included. All results are reported as frequencies and percentages of reports. Results Of 20,765 unique records retrieved, 1189 of them were reviewed for full-text review, of which 76 reports were included. Eight previously published approaches to assessing MQ or reporting guidelines used as proxy to assess RQ were used in 80% (61/76) of identified reports. These included two reporting guidelines (PRISMA and QUOROM) and five quality assessment tools (AMSTAR, R-AMSTAR, OQAQ, Mulrow, Sacks) and GRADE criteria. The remaining 24% (18/76) of reports developed their own criteria. PRISMA, OQAQ, and AMSTAR were the most commonly used published tools to assess MQ or RQ. In conjunction with other approaches, published tools were used in 29% (22/76) of reports, with 36% (8/22) assessing adherence to both PRISMA and AMSTAR criteria and 26% (6/22) using QUOROM and OQAQ. Conclusions The methods used to assess quality of SRs are diverse, and none has become universally accepted. The most commonly used quality assessment tools are AMSTAR, OQAQ, and PRISMA. As new tools and guidelines are developed to improve both the MQ and RQ of SRs, authors of methodological studies are encouraged to put thoughtful consideration into the use of appropriate tools to assess quality and reporting
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