27 research outputs found
Cantonese turn-initial minimal particles: annotation of discourse-interactional functions in dialog corpora
conference pape
The timing bottleneck: Why timing and overlap are mission-critical for conversational user interfaces, speech recognition and dialogue systems
Speech recognition systems are a key intermediary in voice-driven
human-computer interaction. Although speech recognition works well for pristine
monologic audio, real-life use cases in open-ended interactive settings still
present many challenges. We argue that timing is mission-critical for dialogue
systems, and evaluate 5 major commercial ASR systems for their conversational
and multilingual support. We find that word error rates for natural
conversational data in 6 languages remain abysmal, and that overlap remains a
key challenge (study 1). This impacts especially the recognition of
conversational words (study 2), and in turn has dire consequences for
downstream intent recognition (study 3). Our findings help to evaluate the
current state of conversational ASR, contribute towards multidimensional error
analysis and evaluation, and identify phenomena that need most attention on the
way to build robust interactive speech technologies
Pharmacometric Characterization of Dabigatran Hemodialysis
BACKGROUND: Hemodialysis has been shown to be a useful method of decreasing dabigatran plasma levels in situations that require rapid elimination of this thrombin inhibitor. However, there is currently no clinical recommendation for the accelerated/optimized elimination of dabigatran via hemodialysis (e.g., flow rates, filter type, duration of dialysis). OBJECTIVES: The primary objective of the present work was to characterize, via pharmacometric methods, the effects of different blood flow rates in hemodialysis on the pharmacokinetics of dabigatran, using data from a dedicated phase I dialysis study of end-stage renal disease (ESRD) patients. In addition, the effects of various clinically relevant hemodialysis settings were evaluated by simulation to assess their potential use in non-ESRD situations. METHODS: Seven patients with ESRD were investigated in an open-label, fixed-sequence, two-period comparison trial. A population pharmacokinetic model was developed to fit the data and then used for various simulations. Data analyses were performed using NONMEM(®), Berkeley Madonna, or SAS. RESULTS: The pharmacokinetics of dabigatran were best described by a two-compartment model with first-order absorption and a lag time. In addition to total body clearance in ESRD subjects, a first-order dialysis clearance was implemented which was greater than zero during hemodialysis and zero during the interdialytic periods. The relationship between the dialysis clearance and the blood flow rate was best described by the Michaels function. Simulations showed that varying clinically relevant dialysis settings such as filter properties or flow rates had only minor effects. Dialysis duration had the strongest impact on dabigatran plasma concentration. The observed geometric mean redistribution effect after hemodialysis was low (<16 %). The final model was successfully evaluated through the prediction of plasma concentrations from a case report undergoing dialysis. CONCLUSIONS: This analysis allowed the influences of various hemodialysis parameters on the dabigatran plasma concentration to be predicted in detail for the first time. Dialysis duration was identified as having the strongest impact on the reduction in dabigatran plasma concentration. The model developed here can potentially serve as a tool to provide guidance when considering the use of hemodialysis in patients who have received dabigatran
Aetiology of community-acquired, acute gastroenteritis in hospitalised adults: a prospective cohort study
<p>Abstract</p> <p>Background</p> <p>The aetiology of severe gastroenteritis leading to hospitalisation in adults frequently remains unclear. Our objective was to study the causes and characteristics of community-acquired, acute gastroenteritis in adult hospitalized patients to support the clinical management of these patients.</p> <p>Methods</p> <p>From August 2005 to August 2007, we conducted a prospective cohort study among patients ≥18 y hospitalized with community-acquired gastroenteritis in a university hospital in Berlin, Germany. Stool specimens were examined for 26 gastrointestinal pathogens, supplemented by serologic tests for antibodies to <it>Campylobacter spp.</it>, <it>Yersinia spp.</it>, and <it>Entamoeba histolytica</it>. Patient data on demographics and clinical presentation were recorded and analyzed. Coexisting medical conditions were assessed using the Charlson Comorbidity Index score.</p> <p>Results</p> <p>Of 132 patients presenting with acute community-acquired gastroenteritis, 104 were included in the study. A non-infectious aetiology was diagnosed in 8 patients (8%). In 79 (82%) of the remaining 96 patients at least one microorganism was identified. <it>Campylobacter spp. </it>(35%) was detected most frequently, followed by norovirus (23%), <it>Salmonella spp. </it>(20%), and rotavirus (15%). In 46% of the patients with <it>Campylobacter spp. </it>infection, the diagnosis was made solely by serology. More than one pathogen was found in seventeen (22%) patients. Simultaneous infection was significantly more likely in patients with rotavirus and salmonella infections (RR 3.6; 95% CI: 1.8–7.4; RR 2.5; 95%CI: 1.2–5.5). Length of hospital stay (median: 5.5 days) was independent of the pathogen, but was associated with coexisting medical conditions (OR 4,8; 95%CI:2,0–11,6).</p> <p>Conclusion</p> <p>Known enteric pathogens were detected in 82% of adult patients who were hospitalized with acute gastroenteritis. We found that currently used culture-based methods may miss a substantial proportion of <it>Campylobacter </it>infections, and additional serological testing for <it>Campylobacter </it>should be considered. Viral infections emerged as an important cause of severe gastroenteritis in adults, and viral-bacterial co-infections in adults are probably underrecognized so far. The presence of coexisting medical conditions – but not the etiological agent – was a predictor for the duration of the hospital stay.</p
Action formation with janwai in Cantonese Chinese conversation
This thesis describes action formation and ascription featuring the Cantonese Chinese discourse marker janwai ("because") in naturally-occurring Cantonese talk-in-interaction. Conceived as a conversation analytic exploratory data analysis, the study examines the use of this utterance as part of the formation of turns and turn construction units in a naturalistic setting. The study is grounded in MYCanCor, a video corpus of around 20 hours of spontaneous everyday conversation that was collected as part of the study in the Malaysian Cantonese speech community. The thesis describes the use of janwai in four sequential environments, (1) the production of responses that begin with janwai, (2) the production of responses that feature janwai, (3) the production of turns and TCUs that feature janwai but that do not ostensibly constitute responses, and (4) the production of janwai in various other sequential environments, such as to format repairs and noun phrases of cause or reason in clauses. Based on the analysis of the sequential unfolding of stretches of talk-in-interaction, the thesis identifies and explicates different sets of relevance rules that appear to underpin these usage environments. This analysis presents evidence that, as part of question-response sequences, janwai can constitute an affirmative response in turn-initial position and project the forthcoming of a telling or an account either in turn-initial position or after a response token. As part of action formation, janwai appears to be related to conversational accounting and may be deployed either after a displayed intelligibility problem to preface an account or as a device to retrospectively change action formation of the preceding turn as seeking or requiring an account. These findings show that the study of grammar as an emergent, real-world phenomenon can lead to new and unexpected insights in interactional properties of causal discourse markers and thereby contribute to a better understanding of how these utterances serves as a resource that participants deploy to form turns-at-talk, negotiate social action and accomplish interactional tasks. Based on these findings, I conclude with outlining how discourse-interactional functions of janwai may be captured as part of dialogic construction grammars.Doctor of Philosoph
Rethinking open source generative AI: open-washing and the EU AI Act
The past year has seen a steep rise in generative AI systems that claim to be open. But how open are they really? The question of what counts as open source in generative AI is poised to take on particular importance in light of the upcoming EU AI Act that regulates open source systems differently, creating an urgent need for practical openness assessment. Here we use an evidence-based framework that distinguishes 14 dimensions of openness, from training datasets to scientific and technical documentation and from licensing to access methods. Surveying over 45 generative AI systems (both text and text-to-image), we find that while the term open source is widely used, many models are `open weight' at best and many providers seek to evade scientific, legal and regulatory scrutiny by withholding information on training and fine-tuning data. We argue that openness in generative AI is necessarily composite (consisting of multiple elements) and gradient (coming in degrees), and point out the risk of relying on single features like access or licensing to declare models open or not. Evidence-based openness assessment can help foster a generative AI landscape in which models can be effectively regulated, model providers can be held accountable, scientists can scrutinise generative AI, and end users can make informed decisions