Acoustic keyword spotting in speech with applications to data mining

Keyword Spotting is the task of detecting keywords of interest within continu- ous speech. The applications of this technology range from call centre dialogue systems to covert speech surveillance devices. Keyword spotting is particularly well suited to data mining tasks such as real-time keyword monitoring and unre- stricted vocabulary audio document indexing. However, to date, many keyword spotting approaches have su®ered from poor detection rates, high false alarm rates, or slow execution times, thus reducing their commercial viability. This work investigates the application of keyword spotting to data mining tasks. The thesis makes a number of major contributions to the ¯eld of keyword spotting. The ¯rst major contribution is the development of a novel keyword veri¯cation method named Cohort Word Veri¯cation. This method combines high level lin- guistic information with cohort-based veri¯cation techniques to obtain dramatic improvements in veri¯cation performance, in particular for the problematic short duration target word class. The second major contribution is the development of a novel audio document indexing technique named Dynamic Match Lattice Spotting. This technique aug- ments lattice-based audio indexing principles with dynamic sequence matching techniques to provide robustness to erroneous lattice realisations. The resulting algorithm obtains signi¯cant improvement in detection rate over lattice-based audio document indexing while still maintaining extremely fast search speeds. The third major contribution is the study of multiple veri¯er fusion for the task of keyword veri¯cation. The reported experiments demonstrate that substantial improvements in veri¯cation performance can be obtained through the fusion of multiple keyword veri¯ers. The research focuses on combinations of speech background model based veri¯ers and cohort word veri¯ers. The ¯nal major contribution is a comprehensive study of the e®ects of limited training data for keyword spotting. This study is performed with consideration as to how these e®ects impact the immediate development and deployment of speech technologies for non-English languages.

Vision-based classification of solder joint defects

Inspection of solder joints has been a critical process in the electronic manufacturing industry to reduce manufacturing cost, improve yield, and ensure product quality and reliability. The solder joint inspection problem is more challenging than many other visual inspections because of the variability in the appearance of solder joints. Although many research works and various techniques have been developed to classify defect in solder joints, these methods have complex systems of illumination for image acquisition and complicated classification algorithms. An important stage of the analysis is to select the right method for the classification. Better inspection technologies are needed to fill the gap between available inspection capabilities and industry systems. This dissertation aims to provide a solution that can overcome some of the limitations of current inspection techniques. This research proposes two inspection steps for automatic solder joint classification system. The “front-end” inspection system includes illumination normalisation, localization and segmentation. The illumination normalisation approach can effectively and efficiently eliminate the effect of uneven illumination while keeping the properties of the processed image. The “back-end” inspection involves the classification of solder joints by using Log Gabor filter and classifier fusion. Five different levels of solder quality with respect to the amount of solder paste have been defined. Log Gabor filter has been demonstrated to achieve high recognition rates and is resistant to misalignment. Further testing demonstrates the advantage of Log Gabor filter over both Discrete Wavelet Transform and Discrete Cosine Transform. Classifier score fusion is analysed for improving recognition rate. Experimental results demonstrate that the proposed system improves performance and robustness in terms of classification rates. This proposed system does not need any special illumination system, and the images are acquired by an ordinary digital camera. In fact, the choice of suitable features allows one to overcome the problem given by the use of non complex illumination systems. The new system proposed in this research can be incorporated in the development of an automated non-contact, non-destructive and low cost solder joint quality inspection system.

A new pulsed power supply topology based on positive buck-boost converters concept

Improving efficiency and flexibility in pulsed power supply technologies is the most substantial concern of pulsed power systems specifically with regard to plasma generation. Recently, the improvement of pulsed power supply has become of greater concern due to the extension of pulsed power applications to environmental and industrial areas. With this respect, a current source based topology is proposed in this paper as a pulsed power supply which gives the possibility of power flow control during load supplying mode. The main contribution in this configuration is utilization of low-medium voltage semiconductor switches for high voltage generation. A number of switch-diode-capacitor units are designated at the output of topology to exchange the current source energy into voltage form and generate a pulsed power with sufficient voltage magnitude and stress. Simulations carried out in Matlab/SIMULINK platform as well as experimental tests on a prototype setup have verified the capability of this topology in performing desired duties. Being efficient and flexible are the main advantages of this topology.

The contemporary librarian : skills, knowledge and attributes required in a world of emerging technologies

Seventy-six librarians participated in a series of focus groups in support of research exploring the skills, knowledge and attributes required by the contemporary library and information professional in a world of every changing technology. The project was funded by the Australian Learning and Teaching Council. Text data mining analysis revealed three main thematic clusters (libraries, people, jobs) and one minor thematic cluster (community). Library 2.0 was broadly viewed by participants as being about change whilst librarian 2.0 was perceived by participants as not a new creation but just about good librarian practices. Participants expressed the general belief that personality traits, not just qualifications, were critical to be a successful librarian or information worker in the future.

Information and communication technologies : catalysts for sustainable development

The concept of sustainable urban development has been pushed to the forefront of policy-making and politics as the world wakes up to the impacts of climate change and the effects of modern urban lifestyles. Today, sustainable development has become a very prominent element in the day-to-day debate on urban policy and the expression of that policy in urban planning and development decisions. As a result of this, during the last few years, sustainable development automation applications such as sustainable urban development decision support systems have become popular tools as they offer new opportunities for local governments to realise their sustainable development agendas. This chapter explores a range of issues associated with the application of information and communication technologies and decision support systems in the process of underpinning sustainable urban development. The chapter considers how information and communication technologies can be applied to enhance urban planning, raise environmental awareness, share decisions and improve public participation. It introduces and explores three web-based geographical information systems projects as best practice. These systems are developed as support tools to include public opinion in the urban planning and development processes, and to provide planners with comprehensive tools for the analysis of sustainable urban development variants in order to prepare the best plans for constructing sustainable urban communities and futures.

Color and texture feature fusion using kernel PCA with application to object-based vegetation species classification

A good object representation or object descriptor is one of the key issues in object based image analysis. To effectively fuse color and texture as a unified descriptor at object level, this paper presents a novel method for feature fusion. Color histogram and the uniform local binary patterns are extracted from arbitrary-shaped image-objects, and kernel principal component analysis (kernel PCA) is employed to find nonlinear relationships of the extracted color and texture features. The maximum likelihood approach is used to estimate the intrinsic dimensionality, which is then used as a criterion for automatic selection of optimal feature set from the fused feature. The proposed method is evaluated using SVM as the benchmark classifier and is applied to object-based vegetation species classification using high spatial resolution aerial imagery. Experimental results demonstrate that great improvement can be achieved by using proposed feature fusion method.

Sustainable urban and regional infrastructure development : technologies, applications and management

Sustainable Urban and Regional Infrastructure Development: Technologies, Applications and Management, bridges the gap in the current literature by addressing the overall problems present in society's major infrastructures, and the technologies that may be applied to overcome these problems. It focuses on ways in which energy intensive but 'invisible' (to the general public) facilities can become green or greener. The studies presented re lessons to be learnt from our neighbors and from our own backyard, and provide an excellent general overview of the issues facing us all.

Preface : sustainable urban and regional infrastructure development : technologies, applications and management

The concept of ‘sustainability’ has been pushed to the forefront of policy-making and politics as the world wakes up to the impacts of climate change and the effects of the modern urban lifestyle. Climate change has emerged to be one of the biggest challenges faced by our planet today, threatening both built and natural systems with long term consequences which may be irreversible. While there is a vast literature in the market on sustainable cities and urban development, there is currently none that bring together the vital issues of urban and regional development, and the planning, management and implementation of sustainable infrastructure. Large scale infrastructure plays an important part in modern society by not only promoting economic growth, but also by acting as a key indicator for it. More importantly, it supplies municipal/local amenity and services: water, electricity, social and communication facilities, waste removal, transport of people and goods, as well as numerous other services. For the most part, infrastructure has been built by teams lead by engineers who are more concerned about functionality than the concept of sustainability. However, it has been widely stated that current practices and lifestyle cannot continue if we are to leave a healthy living planet to not only the next generation, but also to the generations beyond. Therefore, in order to be sustainable, there are drastic measures that need to be taken. Current single purpose and design infrastructures that are open looped are not sustainable; they are too resource intensive, consume too much energy and support the consumption of natural resources at a rate that will exhaust their supply. Because of this, it is vital that modern society, policy-makers, developers, engineers and planners become pioneers in introducing and incorporating sustainable features into urban and regional infrastructure.