Public Health and Epidemiology Informatics: Recent Research and Trends in the United States

Objectives To survey advances in public health and epidemiology informatics over the past three years. Methods We conducted a review of English-language research works conducted in the domain of public health informatics (PHI), and published in MEDLINE between January 2012 and December 2014, where information and communication technology (ICT) was a primary subject, or a main component of the study methodology. Selected articles were synthesized using a thematic analysis using the Essential Services of Public Health as a typology. Results Based on themes that emerged, we organized the advances into a model where applications that support the Essential Services are, in turn, supported by a socio-technical infrastructure that relies on government policies and ethical principles. That infrastructure, in turn, depends upon education and training of the public health workforce, development that creates novel or adapts existing infrastructure, and research that evaluates the success of the infrastructure. Finally, the persistence and growth of infrastructure depends on financial sustainability. Conclusions Public health informatics is a field that is growing in breadth, depth, and complexity. Several Essential Services have benefited from informatics, notably, “Monitor Health,” “Diagnose & Investigate,” and “Evaluate.” Yet many Essential Services still have not yet benefited from advances such as maturing electronic health record systems, interoperability amongst health information systems, analytics for population health management, use of social media among consumers, and educational certification in clinical informatics. There is much work to be done to further advance the science of PHI as well as its impact on public health practice

¿Cómo afecta la traducción automática y la posedición a la gestión de proyectos? Un enfoque interdisciplinar

Machine translation (MT) and post-editing (PE) are two services that are increasingly in demand in the translation industry. In a context in which large-scale projects are required within tight deadlines, the deployment of this technology to increase productivity is a reality. However, this increase in productivity can only be achieved with appropriate management of the project: MT must not be understood as a tool, but as a process,and project managers, who are usually responsible for the project from start to finish, have to cope with new MT and PE workflows that pose different challenges. Although much has been written about the use of MT and PE in professional practice (resulting in different lines of research in this field), little attention has been paid to the role of the project manager in MT and PE projects. For this reason, the main objective of this paper is to analyse how MT and PE affect the factors that project managers must keep in mind when managing projects, taking as a starting point the most important reference frameworks in project management. The main objective is to offer an interdisciplinary perspective that explains the new challenges the industry is facing and how these challenges affect the different stakeholders involved in the project.La traducción automática (TA) y la posedición (PE) son dos servicios cada vez más demandados en el sector de la traducción. El uso de esta tecnología para conseguir un aumento de la productividad se ha convertido en una realidad en un contexto en el que se precisan proyectos a gran escala con unos plazos muy ajustados. Sin embargo, este aumento de la productividad solo es posible con una correcta gestión del proyecto: la TA no se debe entender como una herramienta, sino como un proceso, y los gestores de proyectos, que son los encargados del proyecto de principio a fin, tienen que hacer frente a nuevos flujos de trabajo de TA y PE que presentan diferentes desafíos. Aunque se ha investigado mucho sobre el uso de la TA y la PE en la práctica profesional (lo que ha dado lugar a diferentes líneas de investigación en este campo), se ha prestado poca atención al papel del gestor de proyectos en los proyectos de TA y PE. Por este motivo, el objetivo de este trabajo es analizar cómo la TA y la PE afectan a los factores que los gestores de proyectos deben tener en cuenta, tomando como punto de partida los marcos de referencia en gestión de proyectos más importantes. El objetivo principal es ofrecer una perspectiva interdisciplinar que explique los retos a los que hace frente la industria y cómo dichos retos afectan a los diferentes agentes implicados en el proyecto

Machine translation and post-editing training as part of a master’s programme

This article presents a description of a machine translation (MT) and post-editing course (PE), along with an MT project management module, that have been introduced in the Localisation Master’s programme at Universitat Autònoma de Barcelona in 2009 and in 2017 respectively. It covers the objectives and structure of the modules, as well as the theoretical and practical components. Additionally, it describes the project-based learning approach implemented in one of the modules, which seeks to foster creative and independent thinking, teamwork, and problem solving in unfamiliar situations, with a view to acquiring transferable skills that are likely to be in demand, regardless of the technological advances taking place in the translation industry

Dodging the Data Bottleneck: Automatic Subtitling with Automatically Segmented ST Corpora

Speech translation for subtitling (SubST) is the task of automatically translating speech data into well-formed subtitles by inserting subtitle breaks compliant to specific displaying guidelines. Similar to speech translation (ST), model training requires parallel data comprising audio inputs paired with their textual translations. In SubST, however, the text has to be also annotated with subtitle breaks. So far, this requirement has represented a bottleneck for system development, as confirmed by the dearth of publicly available SubST corpora. To fill this gap, we propose a method to convert existing ST corpora into SubST resources without human intervention. We build a segmenter model that automatically segments texts into proper subtitles by exploiting audio and text in a multimodal fashion, achieving high segmentation quality in zero-shot conditions. Comparative experiments with SubST systems respectively trained on manual and automatic segmentations result in similar performance, showing the effectiveness of our approach.Comment: Accepted to AACL 202

Dodging the Data Bottleneck: Automatic Subtitling with Automatically Segmented ST Corpora

Speech translation for subtitling (SubST) is the task of automatically translating speech data into well-formed subtitles by inserting subtitle breaks compliant to specific displaying guidelines. Similar to speech translation (ST), model training requires parallel data comprising audio inputs paired with their textual translations. In SubST, however, the text has to be also annotated with subtitle breaks. So far, this requirement has represented a bottleneck for system development, as confirmed by the dearth of publicly available SubST corpora. To fill this gap, we propose a method to convert existing ST corpora into SubST resources without human intervention. We build a segmenter model that automatically segments texts into proper subtitles by exploiting audio and text in a multimodal fashion, achieving high segmentation quality in zero-shot conditions. Comparative experiments with SubST systems respectively trained on manual and automatic segmentations result in similar performance, showing the effectiveness of our approach

Machine-assisted translation by Human-in-the-loop Crowdsourcing for Bambara

Language is more than a tool of conveying information; it is utilized in all aspects of our lives. Yet only a small number of languages in the 7,000 languages worldwide are highly resourced by human language technologies (HLT). Despite African languages representing over 2,000 languages, only a few African languages are highly resourced, for which there exists a considerable amount of parallel digital data. We present a novel approach to machine translation (MT) for under-resourced languages by improving the quality of the model using a paradigm called ``humans in the Loop.\u27\u27 This thesis describes the work carried out to create a Bambara-French MT system including data discovery, data preparation, model hyper-parameter tuning, the development of a crowdsourcing platform for humans in the loop, vocabulary sizing, and segmentation. We present a novel approach to machine translation (MT) for under-resourced languages by improving the quality of the model using a paradigm called ``humans in the Loop.\u27\u27 We achieved a BLEU (bilingual evaluation understudy) score of 17.5. The results confirm that MT for Bambara, despite our small data set, is viable. This work has the potential to contribute to the reduction of language barriers between the people of Sub-Saharan Africa and the rest of the world