A Challenge Set Approach to Evaluating Machine Translation

Neural machine translation represents an exciting leap forward in translation quality. But what longstanding weaknesses does it resolve, and which remain? We address these questions with a challenge set approach to translation evaluation and error analysis. A challenge set consists of a small set of sentences, each hand-designed to probe a system's capacity to bridge a particular structural divergence between languages. To exemplify this approach, we present an English-French challenge set, and use it to analyze phrase-based and neural systems. The resulting analysis provides not only a more fine-grained picture of the strengths of neural systems, but also insight into which linguistic phenomena remain out of reach.Comment: EMNLP 2017. 28 pages, including appendix. Machine readable data included in a separate file. This version corrects typos in the challenge se

Voices of Ancient Women: Stories and Essays on Persephone and Medusa

This thesis combines art historical analysis and creative writing in a collection of essays and short stories centered on the myths of Persephone and Medusa. Ancient art, text, and context is considered in the essays, while the stories approach these subjects on a more contemporary and personal level

Towards an Automatic Dictation System for Translators: the TransTalk Project

Professional translators often dictate their translations orally and have them typed afterwards. The TransTalk project aims at automating the second part of this process. Its originality as a dictation system lies in the fact that both the acoustic signal produced by the translator and the source text under translation are made available to the system. Probable translations of the source text can be predicted and these predictions used to help the speech recognition system in its lexical choices. We present the results of the first prototype, which show a marked improvement in the performance of the speech recognition task when translation predictions are taken into account.Comment: Published in proceedings of the International Conference on Spoken Language Processing (ICSLP) 94. 4 pages, uuencoded compressed latex source with 4 postscript figure

Ion Microscopy in Biology

Ion microscopy, a mass spectrometry based isotopic imaging technique, is uniquely suited for ion transport-related problems in biological systems. Due to its high sensitivity, it can image the transport and distribution of both major and minor elements (isotopes) at subcellular resolutions. The images of major elements such as K, Na, Cl, etc., can be viewed directly and recorded in real-time from the microchannel plate-fluorescent screen detector of the instrument. The low concentration physiologically important elements, such as Ca, need about one minute of integration for good quality imaging. The isotopic imaging capability of ion microscopy provides a unique approach for the use of stable isotopes as tracers. In this way, one can image both the endogenous and the transported isotopes independently. Strict cryogenic sample preparations are essential for ion transport studies. Correlative imaging of the same cell with laser scanning confocal microscopy and ion microscopy can positively identify smaller cytoplasmic compartments such as the Golgi apparatus in calcium images. We have identified the Golgi apparatus as a calcium storing organelle. Another unique application of ion microscopy is the imaging of boron from boronated drugs used in Boron Neutron Capture Therapy (BNCT) of cancer. Ion microscopy is capable of rapid screening of potential drugs for BNCT. This critical information is essential for the fundamental understanding of BNCT. Ion microscopy is now at the stage where it can provide previously unattainable answers to important biomedical questions

Steady and delayed: explaining the different development of meta-ethnography in health care and education

Since its inception in the 1980s, the meta-ethnography approach for synthesising qualitative study accounts has been used extensively in health and social care research and to a lesser extent in educational research. The aim of this article is to reflect on the evolution of the method in both fields. It starts by describing the meta-ethnography approach, charts the rise of evidence-based research in health-related research, and explores the growth in the rate of published health-related meta-ethnographies. It proceeds by offering some explanation for the slower growth in the use of meta-ethnography in educational research. It explains this using the history of the early developments of qualitative approaches in Education and their underpinning paradigms. It then discusses key meta-ethnographies conducted in education, comparing those to more recent ones, in terms of methodological development. The article concludes by drawing lessons about how the conduct of meta-ethnography may be improved in any discipline

Rehabilitation for improving automobile driving after stroke

Publisher version made available in accordance with the publisher's policy. This item is under embargo for a period of 12 months from the date of publication, in accordance with the publisher's policy. 'This review is published as a Cochrane Review in the Cochrane Database of Systematic Reviews 2014, Issue 2. Cochrane Reviews are regularly updated as new evidence emerges and in response to comments and criticisms, and the Cochrane Database of Systematic Reviews should be consulted for the most recent version of the Review.’Background Interventions to improve driving ability after stroke, incl uding driving simulation and retraining visual skills, hav e limited evaluation of their effectiveness to guide policy and practice. Objectives To determine whether any intervention, with the specific aim o f maximising driving skills, improves the driving performa nce of people after stroke. Search methods WesearchedtheCochrane Stroke GroupTrialsregister(August 2 013), theCochrane Central Registerof ControlledTrials( The Cochrane Library 2012, Issue 3), MEDLINE (1950 to October 2013), EMBASE (1980 to Octo ber 2013), and six additional databases. To identify further published, unpublished and ongoing trial s, we handsearched relevant journals and conference proceeding s, searched trials and research registers, checked reference lists and conta cted key researchers in the area. Selection criteria Randomised controlled trials (RCTs), quasi-randomised trials and cluster studies of rehabilitation interventions, with t he specific aim of maximising driving skills or with an outcome of assessing d riving skills in adults after stroke. The primary outcome of i nterest was the performance in an on-road assessment after training. Secon dary outcomes included assessments of vision, cognition and dr iving behaviour. Data collection and analysis Two review authors independently selected trials based on pr e-defined inclusion criteria, extracted the data and assessed ri sk of bias. A third review author moderated disagreements as required. T he review authors contacted all investigators to obtain missi ng information. Main results We included four trials involving 245 participants in the revi ew. Study sample sizes were generally small, and interventi ons, controls and outcome measures varied, and thus it was inappropriate to pool studies. Included studies were at a low risk of bias for th e majority of domains, with a high/unclear risk of bias identified in the a reas of: performance (participants not blinded to allocation), a nd attrition (incomplete outcome data due to withdrawal) bias. Interventio n approaches included the contextual approach of driving simula tion and underlying skill development approach, including the ret raining of speed of visual processing and visual motor skills . The studies were conducted with people who were relatively young and the ti ming after stroke was varied. Primary outcome: there was no cle ar evidence of improved on-road scores immediately after trainin g in any of the four studies, or at six months (mean difference 15 points on the Test Ride for Investigating Practical Fitness to Drive - Belgian version, 95% confidence intervals (CI) 4.56 to 34.56, P v alue = 0.15, one study, 83 participants). Secondary outcomes: road sig n recognition was better in people who underwent training comp ared with control (mean difference 1.69 points on the Road Sign Recogn ition Task of the Stroke Driver Screening Assessment, 95% CI 0 .51 to 2.87, P value = 0.007, one study, 73 participants). Significan t findings were in favour of a simulator-based driving rehabil itation programme (based on one study with 73 participants) but these r esults should be interpreted with caution as they were based o n a single study. Adverse effects were not reported. There was insufficie nt evidence to draw conclusions on the effects on vision, other me asures of cognition, motor and functional activities, and driving beh aviour with the intervention. Authors’ conclusions There was insufficient evidence to reach conclusions about the use of rehabilitation to improve on-road driving skills after st roke. We found limited evidence that the use of a driving simulator m ay be beneficial in improving visuocognitive abilities, such as road sign recognition that are related to driving. Moreover, we we re unable to find any RCTs that evaluated on-road driving lesso ns as an intervention. At present, it is unclear which impairments tha t influence driving ability after stroke are amenable to rehab ilitation, and whether the contextual or remedial approaches, or a combinatio n of both, are more efficacious

Auditory-visual virtual reality as a diagnostic and therapeutic tool for cynophobia

International audienceTraditionally, virtual reality exposure-based treatment concentrates primarily on the presentation of a high fidelity visual experience. However, adequately combining the visual and the auditory experience provides a powerful tool to enhance sensory processing and modulate attention. We present the design and usability testing of an auditory-visual interactive environment for investigating virtual reality exposurebased treatment for cynophobia. The specificity of our application is that it involves 3D sound, allowing the presentations and spatial manipulation of a fearful stimulus in the auditory modality, in the visual modality, and both. We conducted an evaluation test with 10 dog fearful participants in order to assess the capacity of our auditory-visual virtual environment to generate fear reactions. The specific perceptual characteristics of the dog model that were implemented in the virtual environment were highly arousing, suggesting that virtual reality is a promising tool to treat cynophobia

Experience with Adults Shapes Multisensory Representation of Social Familiarity in the Brain of a Songbird

Social animals learn to perceive their social environment, and their social skills and preferences are thought to emerge from greater exposure to and hence familiarity with some social signals rather than others. Familiarity appears to be tightly linked to multisensory integration. The ability to differentiate and categorize familiar and unfamiliar individuals and to build a multisensory representation of known individuals emerges from successive social interactions, in particular with adult, experienced models. In different species, adults have been shown to shape the social behavior of young by promoting selective attention to multisensory cues. The question of what representation of known conspecifics adult-deprived animals may build therefore arises. Here we show that starlings raised with no experience with adults fail to develop a multisensory representation of familiar and unfamiliar starlings. Electrophysiological recordings of neuronal activity throughout the primary auditory area of these birds, while they were exposed to audio-only or audiovisual familiar and unfamiliar cues, showed that visual stimuli did, as in wild-caught starlings, modulate auditory responses but that, unlike what was observed in wild-caught birds, this modulation was not influenced by familiarity. Thus, adult-deprived starlings seem to fail to discriminate between familiar and unfamiliar individuals. This suggests that adults may shape multisensory representation of known individuals in the brain, possibly by focusing the young’s attention on relevant, multisensory cues. Multisensory stimulation by experienced, adult models may thus be ubiquitously important for the development of social skills (and of the neural properties underlying such skills) in a variety of species

No need to Talk, I Know You: Familiarity Influences Early Multisensory Integration in a Songbird's Brain

It is well known that visual information can affect auditory perception, as in the famous “McGurk effect,” but little is known concerning the processes involved. To address this issue, we used the best-developed animal model to study language-related processes in the brain: songbirds. European starlings were exposed to audiovisual compared to auditory-only playback of conspecific songs, while electrophysiological recordings were made in their primary auditory area (Field L). The results show that the audiovisual condition modulated the auditory responses. Enhancement and suppression were both observed, depending on the stimulus familiarity. Seeing a familiar bird led to suppressed auditory responses while seeing an unfamiliar bird led to response enhancement, suggesting that unisensory perception may be enough if the stimulus is familiar while redundancy may be required for unfamiliar items. This is to our knowledge the first evidence that multisensory integration may occur in a low-level, putatively unisensory area of a non-mammalian vertebrate brain, and also that familiarity of the stimuli may influence modulation of auditory responses by vision

Automatic Alarm Correlation for Fault Identification *

Abstract In communication networks, a large number of alarms exist to signal any abnormal behavior of the network. As network faults typically result in a number of alarms, correlating these different alarms and identifying their source is a major problem in fault management. The alarm correlation problem is of major practical significance. Alarms that have not been correlated may not only lead to significant misdirected efforts, based on insufficient information, but may cause multiple COTrective actions (possibly contradictory) as each alert is handled independently. This paper proposes a general framework to solve the alarm correlation problem. We introduce a new model for faults and alarms based on probabilistic finite state machines. We propose two algorithms. The first one acquires the fault models starting from possibly incomplete and incorrect data. The second one correlates alarms in the presence of multiple faults and noisy information. Both algorithms have polynomial time complexity, use an extension of the Viterbi algorithm to deal with the corrupted data, and can be implemented in hardware. As an example, they are applied to analyze faults using data generated by the ANS (Advanced Network and Services, Inc.)/NSF T 3 network