PLDA based speaker recognition on short utterances

This paper investigates the effects of limited speech data in the context of speaker verification using a probabilistic linear discriminant analysis (PLDA) approach. Being able to reduce the length of required speech data is important to the development of automatic speaker verification system in real world applications. When sufficient speech is available, previous research has shown that heavy-tailed PLDA (HTPLDA) modeling of speakers in the i-vector space provides state-of-the-art performance, however, the robustness of HTPLDA to the limited speech resources in development, enrolment and verification is an important issue that has not yet been investigated. In this paper, we analyze the speaker verification performance with regards to the duration of utterances used for both speaker evaluation (enrolment and verification) and score normalization and PLDA modeling during development. Two different approaches to total-variability representation are analyzed within the PLDA approach to show improved performance in short-utterance mismatched evaluation conditions and conditions for which insufficient speech resources are available for adequate system development. The results presented within this paper using the NIST 2008 Speaker Recognition Evaluation dataset suggest that the HTPLDA system can continue to achieve better performance than Gaussian PLDA (GPLDA) as evaluation utterance lengths are decreased. We also highlight the importance of matching durations for score normalization and PLDA modeling to the expected evaluation conditions. Finally, we found that a pooled total-variability approach to PLDA modeling can achieve better performance than the traditional concatenated total-variability approach for short utterances in mismatched evaluation conditions and conditions for which insufficient speech resources are available for adequate system development.

Investigating homework as a social practice : a qualitative approach

This thesis examines the social practice of homework. It explores how homework is shaped by the discourses, policies and guidelines in circulation in a society at any given time with particular reference to one school district in the province of Newfoundland and Labrador, Canada. This study investigates how contemporary homework reconstitutes the home as a pedagogical site where the power of the institution of schooling circulates regularly from school to home. It examines how the educational system shapes the organization of family life and how family experiences with homework may be different in different sites depending on the accessibility of various forms of cultural capital. This study employs a qualitative approach, incorporating multiple case studies, and is complemented by insights from institutional ethnography and critical discourse analysis. It draws on the theoretical concepts of Foucault including power and power relations, and governmentality and surveillance, as well as Bourdieu’s concepts of economic, social and cultural capital for analysis. It employs concepts from Bourdieu’s work as they have been expanded on by researchers including Reay (1998), Lareau (2000), and Griffith and Smith (2005). The studies of these researchers allowed for an examination of homework as it related to families and mothers’ work. Smith’s (1987; 1999) concepts of ruling relations, mothers’ unpaid labour, and the engine of inequality were also employed in the analysis. Family interviews with ten volunteer families, teacher focus group sessions with 15 teachers from six schools, homework artefacts, school newsletters, homework brochures, and publicly available assessment and evaluation policy documents from one school district were analyzed. From this analysis key themes emerged and the findings are documented throughout five data analysis chapters. This study shows a change in education in response to a system shaped by standards, accountability and testing. It documents an increased transference of educational responsibility from one educational stakeholder to another. This transference of responsibility shifts downward until it eventually reaches the family in the form of homework and educational activities. Texts in the form of brochures and newsletters, sent home from school, make available to parents specific subject positions that act as instruments of normalization. These subject positions promote a particular ‘ideal’ family that has access to certain types of cultural capital needed to meet the school’s expectations. However, the study shows that these resources are not equally available to all and some families struggle to obtain what is necessary to complete educational activities in the home. The increase in transference of educational work from the school to the home results in greater work for parents, particularly mothers. As well, consideration is given to mother’s role in homework and how, in turn, classroom instructional practices are sometimes dependent on the work completed at home with differential effects for children. This study confirms previous findings that it is mothers who assume the greatest role in the educational trajectory of their children. An important finding in this research is that it is not only middle-class mothers who dedicate extensive time working hard to ensure their children’s educational success; working-class mothers also make substantial contributions of time and resources to their children’s education. The assignments and educational activities distributed as homework require parents’ knowledge of technical school pedagogy to help their children. Much of the homework being sent home from schools is in the area of literacy, particularly reading, but requires parents to do more than read with children. A key finding is that the practices of parents are changing and being reconfigured by the expectations of schools in regard to reading. Parents are now being required to monitor and supervise children’s reading, as well as help children complete reading logs, written reading responses, and follow up questions. The reality of family life as discussed by the participants in this study does not match the ‘ideal’ as portrayed in the educational documents. Homework sessions often create frustrations and tensions between parents and children. Some of the greatest struggles for families were created by mathematical homework, homework for those enrolled in the French Immersion program, and the work required to complete Literature, Heritage and Science Fair projects. Even when institutionalized and objectified capital was readily available, many families still encountered struggles when trying to carry out the assigned educational tasks. This thesis argues that homework and education-related activities play out differently in different homes. Consideration of this significance may assist educators to better understand and appreciate the vast difference in families and the ways in which each family can contribute to their children’s educational trajectory.

Long exposure localization in darkness using consumer cameras

In this paper we demonstrate passive vision-based localization in environments more than two orders of magnitude darker than the current benchmark using a 100 webcam and a 500 camera. Our approach uses the camera’s maximum exposure duration and sensor gain to achieve appropriately exposed images even in unlit night-time environments, albeit with extreme levels of motion blur. Using the SeqSLAM algorithm, we first evaluate the effect of variable motion blur caused by simulated exposures of 132 ms to 10000 ms duration on localization performance. We then use actual long exposure camera datasets to demonstrate day-night localization in two different environments. Finally we perform a statistical analysis that compares the baseline performance of matching unprocessed greyscale images to using patch normalization and local neighbourhood normalization – the two key SeqSLAM components. Our results and analysis show for the first time why the SeqSLAM algorithm is effective, and demonstrate the potential for cheap camera-based localization systems that function across extreme perceptual change.

Rural self-reliance: the impact on health experiences of people living with type II diabetes in rural Queensland, Australia

Objective: The objective of the study was to explore whether and how rural culture influences type II diabetes management and to better understand the social processes that rural people construct in coping with diabetes and its complications. In particular, the study aimed to analyse the interface and interactions between rural people with type II diabetes and the Australian health care system, and to develop a theoretical understanding that reflects constructs that may be more broadly applicable. Methods: The study applied constructivist grounded theory methods within an interpretive interactionist framework. Data from 39 semi-structured interviews with rural and urban type II diabetes patients and a mix of rural health care providers were analysed to develop a theoretical understanding of the social processes that define diabetes management in that context. Results: The analysis suggests that although type II diabetes imposes limitations that require adjustment and adaptation, these processes are actively negotiated by rural people within the environmental context to fit the salient social understandings of autonomy and self-reliance. Thus, people normalized self-reliant diabetes management behaviours because this was congruent with the rural culture. Factors that informed the actions of normalization were relationships between participants and health care professionals, support, and access to individual resources. Conclusions: The findings point to ways in which rural self-reliance is conceived as the primary strategy of diabetes management. People face the paradox of engaging with a health care system that at the same time maximizes individual responsibility for health and minimizes the social support by which individuals manage the condition. The emphasis on self-reliance gives some legitimacy to a lack of prevention and chronic care services. Success of diabetes management behaviours is, however, contingent on relative resources. Where there is good primary care, there develops a number of downstream effects including a sense of empowerment to manage difficult rural environmental circumstances. This has particular bearing on health outcomes for people with fewer resources.

Addressing accuracy and precision issues in iTRAQ quantitation

iTRAQ (isobaric tags for relative or absolute quantitation) is a mass spectrometry technology that allows quantitative comparison of protein abundance by measuring peak intensities of reporter ions released from iTRAQ-tagged peptides by fragmentation during MS/MS. However, current data analysis techniques for iTRAQ struggle to report reliable relative protein abundance estimates and suffer with problems of precision and accuracy. The precision of the data is affected by variance heterogeneity: low signal data have higher relative variability; however, low abundance peptides dominate data sets. Accuracy is compromised as ratios are compressed toward 1, leading to underestimation of the ratio. This study investigated both issues and proposed a methodology that combines the peptide measurements to give a robust protein estimate even when the data for the protein are sparse or at low intensity. Our data indicated that ratio compression arises from contamination during precursor ion selection, which occurs at a consistent proportion within an experiment and thus results in a linear relationship between expected and observed ratios. We proposed that a correction factor can be calculated from spiked proteins at known ratios. Then we demonstrated that variance heterogeneity is present in iTRAQ data sets irrespective of the analytical packages, LC-MS/MS instrumentation, and iTRAQ labeling kit (4-plex or 8-plex) used. We proposed using an additive-multiplicative error model for peak intensities in MS/MS quantitation and demonstrated that a variance-stabilizing normalization is able to address the error structure and stabilize the variance across the entire intensity range. The resulting uniform variance structure simplifies the downstream analysis. Heterogeneity of variance consistent with an additive-multiplicative model has been reported in other MS-based quantitation including fields outside of proteomics; consequently the variance-stabilizing normalization methodology has the potential to increase the capabilities of MS in quantitation across diverse areas of biology and chemistry.

Reversibility of liver failure secondary to metastatic breast cancer by vinorelbine and cisplatin chemotherapy

Purpose: The development of liver metastases from breast cancer is associated with a very poor prognosis, estimated at 4 months median survival. Since treatment with many chemotherapeutic agents is relatively contraindicated, we assessed the safety, tolerability and potential efficacy of combination chemotherapy with vinorelbine and cisplatin (ViP). Method: Pilot study in 11 patients with histologically confirmed breast carcinoma, radiological evidence of liver metastases and serum bilirubin greater than 1.5 times the upper limit of normal. Patients received up to six cycles of cisplatin (75 mg/m 2) every 21 days and vinorelbine (20 mg/m 2) on days 1 and 8 of every 21-day cycle. Measurement of liver lesions was performed on CT scan every 8 weeks into treatment. Results: The most frequently reported adverse event was myelosuppression. Other adverse effects included nausea, vomiting and mild neurotoxicity. Two patients died after one treatment with ViP, one of whom suffered an intracerebral haemorrhage that was possibly treatment-related. Improvement in liver function tests was observed in 10 patients, and mean time to normalization of bilirubin levels was 36 days. Partial responses were documented radiologically in 7 out of 11 patients treated. Median overall survival from trial entry was 6.5 months (range 11-364 days), with one patient alive 13 months from trial entry. Conclusion: Normalization of liver function is possible with ViP treatment of metastatic breast cancer, offering the potential to prolong survival. Phase II clinical trials of this regimen in this patient group should include measurement of quality of life in order to assess risk versus benefit.

An evaluation of different features and learning models for anomalous event detection

The huge amount of CCTV footage available makes it very burdensome to process these videos manually through human operators. This has made automated processing of video footage through computer vision technologies necessary. During the past several years, there has been a large effort to detect abnormal activities through computer vision techniques. Typically, the problem is formulated as a novelty detection task where the system is trained on normal data and is required to detect events which do not fit the learned ‘normal’ model. There is no precise and exact definition for an abnormal activity; it is dependent on the context of the scene. Hence there is a requirement for different feature sets to detect different kinds of abnormal activities. In this work we evaluate the performance of different state of the art features to detect the presence of the abnormal objects in the scene. These include optical flow vectors to detect motion related anomalies, textures of optical flow and image textures to detect the presence of abnormal objects. These extracted features in different combinations are modeled using different state of the art models such as Gaussian mixture model(GMM) and Semi- 2D Hidden Markov model(HMM) to analyse the performances. Further we apply perspective normalization to the extracted features to compensate for perspective distortion due to the distance between the camera and objects of consideration. The proposed approach is evaluated using the publicly available UCSD datasets and we demonstrate improved performance compared to other state of the art methods.

Towards condition-invariant, top-down visual place recognition

In this paper we present a novel place recognition algorithm inspired by recent discoveries in human visual neuroscience. The algorithm combines intolerant but fast low resolution whole image matching with highly tolerant, sub-image patch matching processes. The approach does not require prior training and works on single images (although we use a cohort normalization score to exploit temporal frame information), alleviating the need for either a velocity signal or image sequence, differentiating it from current state of the art methods. We demonstrate the algorithm on the challenging Alderley sunny day – rainy night dataset, which has only been previously solved by integrating over 320 frame long image sequences. The system is able to achieve 21.24% recall at 100% precision, matching drastically different day and night-time images of places while successfully rejecting match hypotheses between highly aliased images of different places. The results provide a new benchmark for single image, condition-invariant place recognition.

Improving short utterance i-vector speaker verification using utterance variance modelling and compensation techniques

This paper proposes techniques to improve the performance of i-vector based speaker verification systems when only short utterances are available. Short-length utterance i-vectors vary with speaker, session variations, and the phonetic content of the utterance. Well established methods such as linear discriminant analysis (LDA), source-normalized LDA (SN-LDA) and within-class covariance normalisation (WCCN) exist for compensating the session variation but we have identified the variability introduced by phonetic content due to utterance variation as an additional source of degradation when short-duration utterances are used. To compensate for utterance variations in short i-vector speaker verification systems using cosine similarity scoring (CSS), we have introduced a short utterance variance normalization (SUVN) technique and a short utterance variance (SUV) modelling approach at the i-vector feature level. A combination of SUVN with LDA and SN-LDA is proposed to compensate the session and utterance variations and is shown to provide improvement in performance over the traditional approach of using LDA and/or SN-LDA followed by WCCN. An alternative approach is also introduced using probabilistic linear discriminant analysis (PLDA) approach to directly model the SUV. The combination of SUVN, LDA and SN-LDA followed by SUV PLDA modelling provides an improvement over the baseline PLDA approach. We also show that for this combination of techniques, the utterance variation information needs to be artificially added to full-length i-vectors for PLDA modelling.

Corneal confocal microscopy detects early nerve regeneration in diabetic neuropathy after simultaneous pancreas and kidney transplantation

Diabetic neuropathy is associated with increased morbidity and mortality. To date, limited data in subjects with impaired glucose tolerance and diabetes demonstrate nerve fiber repair after intervention. This may reflect a lack of efficacy of the interventions but may also reflect difficulty of the tests currently deployed to adequately assess nerve fiber repair, particularly in short-term studies. Corneal confocal microscopy (CCM) represents a novel noninvasive means to quantify nerve fiber damage and repair. Fifteen type 1 diabetic patients undergoing simultaneous pancreas-kidney transplantation (SPK) underwent detailed assessment of neurologic deficits, quantitative sensory testing (QST), electrophysiology, skin biopsy, corneal sensitivity, and CCM at baseline and at 6 and 12 months after successful SPK. At baseline, diabetic patients had a significant neuropathy compared with control subjects. After successful SPK there was no significant change in neurologic impairment, neurophysiology, QST, corneal sensitivity, and intraepidermal nerve fiber density (IENFD). However, CCM demonstrated significant improvements in corneal nerve fiber density, branch density, and length at 12 months. Normalization of glycemia after SPK shows no significant improvement in neuropathy assessed by the neurologic deficits, QST, electrophysiology, and IENFD. However, CCM shows a significant improvement in nerve morphology, providing a novel noninvasive means to establish early nerve repair that is missed by currently advocated assessment techniques.

Penal Culture and Hyperincarceration : the Revival of the Prison

What are the various forces influencing the role of the prison in late modern societies? What changes have there been in penality and use of the prison over the past 40 years that have led to the re-valorization of the prison? Using penal culture as a conceptual and theoretical vehicle, and Australia as a case study, this book analyses international developments in penality and imprisonment. Authored by some of Australia’s leading penal theorists, the book examines the historical and contemporary influences on the use of the prison, with analyses of colonialism, post colonialism, race, and what they term the ‘penal/colonial complex,’ in the construction of imprisonment rates and on the development of the phenomenon of hyperincarceration. The authors develop penal culture as an explanatory framework for continuity, change and difference in prisons and the nature of contested penal expansionism. The influence of transformative concepts such as ‘risk management’, ‘the therapeutic prison’, and ‘preventative detention’ are explored as aspects of penal culture. Processes of normalization, transmission and reproduction of penal culture are seen throughout the social realm. Comparative, contemporary and historical in its approach, the book provides a new analysis of penality in the 21st century.

Practical Advice to Entrepreneurs Series by ACE Adjunct Professor Dean Shepherd: Practical advice on learning the most from project failure

The author, Dean Shepherd, is of entrepreneurship—how entrepreneurs think, decide to act, and feel. He recently realized that while his publications in academic journals have implications for entrepreneurs, those implications have remained relatively hidden in the text of the articles and hidden in articles published in journals largely inaccessible to those involved in the entrepreneurial process. This series is designed to bring the practical implications of his research to the forefront.

Understanding the abnormal brain activity in epilepsy as a potential predictor of the onset of an epileptic seizure

The Brain Research Institute (BRI) uses various types of indirect measurements, including EEG and fMRI, to understand and assess brain activity and function. As well as the recovery of generic information about brain function, research also focuses on the utilisation of such data and understanding to study the initiation, dynamics, spread and suppression of epileptic seizures. To assist with the future focussing of this aspect of their research, the BRI asked the MISG 2010 participants to examine how the available EEG and fMRI data and current knowledge about epilepsy should be analysed and interpreted to yield an enhanced understanding about brain activity occurring before, at commencement of, during, and after a seizure. Though the deliberations of the study group were wide ranging in terms of the related matters considered and discussed, considerable progress was made with the following three aspects. (1) The science behind brain activity investigations depends crucially on the quality of the analysis and interpretation of, as well as the recovery of information from, EEG and fMRI measurements. A number of specific methodologies were discussed and formalised, including independent component analysis, principal component analysis, profile monitoring and change point analysis (hidden Markov modelling, time series analysis, discontinuity identification). (2) Even though EEG measurements accurately and very sensitively record the onset of an epileptic event or seizure, they are, from the perspective of understanding the internal initiation and localisation, of limited utility. They only record neuronal activity in the cortical (surface layer) neurons of the brain, which is a direct reflection of the type of electrical activity they have been designed to record. 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Recursive pathways to marginal likelihood estimation with prior-sensitivity analysis

We investigate the utility to computational Bayesian analyses of a particular family of recursive marginal likelihood estimators characterized by the (equivalent) algorithms known as "biased sampling" or "reverse logistic regression" in the statistics literature and "the density of states" in physics. Through a pair of numerical examples (including mixture modeling of the well-known galaxy dataset) we highlight the remarkable diversity of sampling schemes amenable to such recursive normalization, as well as the notable efficiency of the resulting pseudo-mixture distributions for gauging prior-sensitivity in the Bayesian model selection context. Our key theoretical contributions are to introduce a novel heuristic ("thermodynamic integration via importance sampling") for qualifying the role of the bridging sequence in this procedure, and to reveal various connections between these recursive estimators and the nested sampling technique.

Practical Advice for Entrepreneurs

I am interested in the psychology of entrepreneurship—how entrepreneurs think, decide to act, and feel. I recently realized that while my publications in academic journals have implications for entrepreneurs, those implications have remained relatively hidden in the text of the articles and hidden in articles published in journals largely inaccessible to those involved in the entrepreneurial process. This book is designed to bring the practical implications of my research to the forefront. I decided to take a different approach with this book and not write it for a publisher. I did this because I wanted the ideas to be freely available: (1) I wanted those interested in practical advice for entrepreneurs to be able to freely download, distribute, and use this information (I only ask that the content be properly cited), (2) I wanted to release the chapters independently and make chapters available as they are finished, and; (3) I wanted this work to be a dialogue rather than a one-way conversation—I hope readers email me feedback (positive and negative) so that I can use this information to revise the book. In producing the journal articles underpinning this book, I have had the pleasure of working with many talented and wonderful colleagues—they are cited at the end of each chapter. I hope you find some of the advice in this book useful.