Gamified Speaker Comparison by Listening

We address speaker comparison by listening in a game-like environment, hypothesized to make the task more motivating for naive listeners. We present the same 30 trials selected with the help of an x-vector speaker recognition system from VoxCeleb to a total of 150 crowdworkers recruited through Amazon's Mechanical Turk. They are divided into cohorts of 50, each using one of three alternative interface designs: (i) a traditional (nongamified) design; (ii) a gamified design with feedback on decisions, along with points, game level indications, and possibility for interface customization; (iii) another gamified design with an additional constraint of maximum of 5 'lives' consumed by wrong answers. We analyze the impact of these interface designs to listener error rates (both misses and false alarms), probability calibration, time of quitting, along with survey questionnaire. The results indicate improved performance from (i) to (ii) and (iii), particularly in terms of balancing the two types of detection errors.Comment: Accepted to Odyssey 2022 The Speaker and Language Recognition Worksho

How to construct perfect and worse-than-coin-flip spoofing countermeasures:a word of warning on shortcut learning

Abstract Shortcut learning, or ‘Clever Hans effect’ refers to situations where a learning agent (e.g., deep neural networks) learns spurious correlations present in data, resulting in biased models. We focus on finding shortcuts in deep learning based spoofing countermeasures (CMs) that predict whether a given utterance is spoofed or not. While prior work has addressed specific data artifacts, such as silence, no general normative framework has been explored for analyzing shortcut learning in CMs. In this study, we propose a generic approach to identifying shortcuts by introducing systematic interventions on the training and test sides, including the boundary cases of ‘near-perfect’ and ‘worse than coin flip’ (label flip). By using three different models, ranging from classic to state-of-the-art, we demonstrate the presence of shortcut learning in five simulated conditions. We also analyze the results using a regression model to understand how biases affect the class-conditional score statistics

I4U Submission to NIST SRE 2012: a large-scale collaborative effort for noise-robust speaker verification

I4U is a joint entry of nine research Institutes and Universities across 4 continents to NIST SRE 2012. It started with a brief discussion during the Odyssey 2012 workshop in Singapore. An online discussion group was soon set up, providing a discussion platform for different issues surrounding NIST SRE’12. Noisy test segments, uneven multi-session training, variable enrollment duration, and the issue of open-set identification were actively discussed leading to various solutions integrated to the I4U submission. The joint submission and several of its 17 sub-systems were among top-performing systems. We summarize the lessons learnt from this large-scale effort

Mortality after surgery in Europe: a 7 day cohort study

Background: Clinical outcomes after major surgery are poorly described at the national level. Evidence of heterogeneity between hospitals and health-care systems suggests potential to improve care for patients but this potential remains unconfirmed. The European Surgical Outcomes Study was an international study designed to assess outcomes after non-cardiac surgery in Europe.Methods: We did this 7 day cohort study between April 4 and April 11, 2011. We collected data describing consecutive patients aged 16 years and older undergoing inpatient non-cardiac surgery in 498 hospitals across 28 European nations. Patients were followed up for a maximum of 60 days. The primary endpoint was in-hospital mortality. Secondary outcome measures were duration of hospital stay and admission to critical care. We used χ² and Fisher’s exact tests to compare categorical variables and the t test or the Mann-Whitney U test to compare continuous variables. Significance was set at p<0·05. We constructed multilevel logistic regression models to adjust for the differences in mortality rates between countries.Findings: We included 46 539 patients, of whom 1855 (4%) died before hospital discharge. 3599 (8%) patients were admitted to critical care after surgery with a median length of stay of 1·2 days (IQR 0·9–3·6). 1358 (73%) patients who died were not admitted to critical care at any stage after surgery. Crude mortality rates varied widely between countries (from 1·2% [95% CI 0·0–3·0] for Iceland to 21·5% [16·9–26·2] for Latvia). After adjustment for confounding variables, important differences remained between countries when compared with the UK, the country with the largest dataset (OR range from 0·44 [95% CI 0·19 1·05; p=0·06] for Finland to 6·92 [2·37–20·27; p=0·0004] for Poland).Interpretation: The mortality rate for patients undergoing inpatient non-cardiac surgery was higher than anticipated. Variations in mortality between countries suggest the need for national and international strategies to improve care for this group of patients.Funding: European Society of Intensive Care Medicine, European Society of Anaesthesiology