Combination strategies for a factor analysis phone-conditioned speaker verification system

This work aims to take advantage of recent developments in joint factor analysis (JFA) in the context of a phonetically conditioned GMM speaker verification system. Previous work has shown performance advantages through phonetic conditioning, but this has not been shown to date with the JFA framework. Our focus is particularly on strategies for combining the phone-conditioned systems. We show that the classic fusion of the scores is suboptimal when using multiple GMM systems. We investigate several combination strategies in the model space, and demonstrate improvement over score-level combination as well as over a non-phonetic baseline system. This work was conducted during the 2008 CLSP Workshop at Johns Hopkins University.

Confirmatory factor analysis of the Way of Coping Checklist-Revised (WCCL-R) in the Asian context

Industrial employment growth has been one of the most dynamic areas of expansion in Asia; however, current trends in industrialised working environments have resulted in greater employee stress. Despite research showing that cultural values affect the way people cope with stress, there is a dearth of psychometrically established tools for use in non-Western countries to measure these constructs. Studies of the "Way of Coping Checklist-Revised" (WCCL-R) in the West suggest that the WCCL-R has good psychometric properties, but its applicability in the East is still understudied. A confirmatory factor analysis (CFA) is used to validate the WCCL-R constructs in an Asian population. This study used 1,314 participants from Indonesia, Sri Lanka, Singapore, and Thailand. An initial exploratory factor analysis revealed that original structures were not confirmed; however, a subsequent EFA and CFA showed that a 38-item, five-factor structure model was confirmed. The revised WCCL-R in the Asian sample was also found to have good reliability and sound construct and concurrent validity. The 38-item structure of the WCCL-R has considerable potential in future occupational stress-related research in Asian countries.

Within-session variability modelling for factor analysis speaker verification

This work presents an extended Joint Factor Analysis model including explicit modelling of unwanted within-session variability. The goals of the proposed extended JFA model are to improve verification performance with short utterances by compensating for the effects of limited or imbalanced phonetic coverage, and to produce a flexible JFA model that is effective over a wide range of utterance lengths without adjusting model parameters such as retraining session subspaces. Experimental results on the 2006 NIST SRE corpus demonstrate the flexibility of the proposed model by providing competitive results over a wide range of utterance lengths without retraining and also yielding modest improvements in a number of conditions over current state-of-the-art.

A confirmatory factor analysis of the Toronto Alexithymia Scale (TAS-20) in an alcohol-dependent sample

Confirmatory factor analyses were conducted to evaluate the factorial validity of the Toronto Alexithymia Scale in an alcohol-dependent sample. Several factor models were examined, but all models were rejected given their poor fit. A revision of the TAS-20 in alcohol-dependent populations may be needed.

Governors highway safety associations and transportation planning: Exploratory factor analysis and structural equation modeling

The Intermodal Surface Transportation Efficiency Act (ISTEA) of 1991 mandated the consideration of safety in the regional transportation planning process. As part of National Cooperative Highway Research Program Project 8-44, "Incorporating Safety into the Transportation Planning Process," we conducted a telephone survey to assess safety-related activities and expertise at Governors Highway Safety Associations (GHSAs), and GHSA relationships with metropolitan planning organizations (MPOs) and state departments of transportation (DOTs). The survey results were combined with statewide crash data to enable exploratory modeling of the relationship between GHSA policies and programs and statewide safety. The modeling objective was to illuminate current hurdles to ISTEA implementation, so that appropriate institutional, analytical, and personnel improvements can be made. The study revealed that coordination of transportation safety across DOTs, MPOs, GHSAs, and departments of public safety is generally beneficial to the implementation of safety. In addition, better coordination is characterized by more positive and constructive attitudes toward incorporating safety into planning.

Applying SVMs and weight-based factor analysis to unsupervised adaptation for speaker verification

This paper presents an extended study on the implementation of support vector machine(SVM) based speaker verification in systems that employ continuous progressive model adaptation using the weight-based factor analysis model. The weight-based factor analysis model compensates for session variations in unsupervised scenarios by incorporating trial confidence measures in the general statistics used in the inter-session variability modelling process. Employing weight-based factor analysis in Gaussian mixture models (GMM) was recently found to provide significant performance gains to unsupervised classification. Further improvements in performance were found through the integration of SVM-based classification in the system by means of GMM supervectors. This study focuses particularly on the way in which a client is represented in the SVM kernel space using single and multiple target supervectors. Experimental results indicate that training client SVMs using a single target supervector maximises performance while exhibiting a certain robustness to the inclusion of impostor training data in the model. Furthermore, the inclusion of low-scoring target trials in the adaptation process is investigated where they were found to significantly aid performance.

New edition leaves scope for "human factor" in research

The Media and Communications in Australia, edited by Stuart Cunningham and Graeme Turner (3rd edition). Sydney: Allen and Unwin, 2010, 362 pp. ISBN 978-1 74237-064-4; reviewed by Lee Duffield, Queensland University of Technology.

Risk factor analysis and spatiotemporal CART model of cryptosporidiosis in Queensland, Australia

Background: It remains unclear whether it is possible to develop a spatiotemporal epidemic prediction model for cryptosporidiosis disease. This paper examined the impact of social economic and weather factors on cryptosporidiosis and explored the possibility of developing such a model using social economic and weather data in Queensland, Australia. ----- ----- Methods: Data on weather variables, notified cryptosporidiosis cases and social economic factors in Queensland were supplied by the Australian Bureau of Meteorology, Queensland Department of Health, and Australian Bureau of Statistics, respectively. Three-stage spatiotemporal classification and regression tree (CART) models were developed to examine the association between social economic and weather factors and monthly incidence of cryptosporidiosis in Queensland, Australia. The spatiotemporal CART model was used for predicting the outbreak of cryptosporidiosis in Queensland, Australia. ----- ----- Results: The results of the classification tree model (with incidence rates defined as binary presence/absence) showed that there was an 87% chance of an occurrence of cryptosporidiosis in a local government area (LGA) if the socio-economic index for the area (SEIFA) exceeded 1021, while the results of regression tree model (based on non-zero incidence rates) show when SEIFA was between 892 and 945, and temperature exceeded 32°C, the relative risk (RR) of cryptosporidiosis was 3.9 (mean morbidity: 390.6/100,000, standard deviation (SD): 310.5), compared to monthly average incidence of cryptosporidiosis. When SEIFA was less than 892 the RR of cryptosporidiosis was 4.3 (mean morbidity: 426.8/100,000, SD: 319.2). A prediction map for the cryptosporidiosis outbreak was made according to the outputs of spatiotemporal CART models. ----- ----- Conclusions: The results of this study suggest that spatiotemporal CART models based on social economic and weather variables can be used for predicting the outbreak of cryptosporidiosis in Queensland, Australia.

Improving cyclodiode - a risk factor analysis of complications

PURPOSE: The purpose of this study is to identify risk factors for developing complications following treatment of refractory glaucoma with transscleral diode laser cyclophotocoagulation (cyclodiode), to improve the safety profile of this treatment modality. METHOD: A retrospective analysis of 72 eyes from 70 patients who were treated with cyclodiode. RESULTS: The mean pre-treatment IOP was 37.0 mmHg (SD 11.0), with a mean post-treatment reduction in intraocular pressure (IOP) of 19.8 mmHg, and a mean IOP at last follow-up of 17.1 mmHg (SD 9.7). Mean total power delivered during treatment was 156.8 Joules (SD 82.7) over a mean of 1.3 treatments (SD 0.6). Sixteen eyes (22.2% of patients) developed complications from the treatment, with the most common being hypotony, occurring in 6 patients, including 4 with neovascular glaucoma. A higher pre-treatment IOP and higher mean total power delivery also were associated with higher complications. CONCLUSIONS: Cyclodiode is an effective treatment option for glaucoma that is refractory to other treatment options. By identifying risk factors for potential complications, cyclodiode can be modified accordingly for each patient to improve safety and efficacy.

The "human factor" in DFM

With a focus on understanding the overall effect of DFM on human factors aspects, DFM/DFA literature was systematically searched, reviewed and critically assessed. The influence of DFM on work organization is analysed using examples from literature, with the aim of quantifying consequences on work performance, job satisfaction and human work load where possible. It is also shown that job enlargement through DFM tasks increases the workload for the Product Designer, who is on the critical path of the engineering process. Without taking measures to counterbalance this higher workload of the Product Designer, DFM projects in complex engineering environments are likely to fail.