Automatic spoken language identification utilizing acoustic and phonetic speech information

Automatic spoken Language Identi¯cation (LID) is the process of identifying the language spoken within an utterance. The challenge that this task presents is that no prior information is available indicating the content of the utterance or the identity of the speaker. The trend of globalization and the pervasive popularity of the Internet will amplify the need for the capabilities spoken language identi¯ca- tion systems provide. A prominent application arises in call centers dealing with speakers speaking di®erent languages. Another important application is to index or search huge speech data archives and corpora that contain multiple languages. The aim of this research is to develop techniques targeted at producing a fast and more accurate automatic spoken LID system compared to the previous National Institute of Standards and Technology (NIST) Language Recognition Evaluation. Acoustic and phonetic speech information are targeted as the most suitable fea- tures for representing the characteristics of a language. To model the acoustic speech features a Gaussian Mixture Model based approach is employed. Pho- netic speech information is extracted using existing speech recognition technol- ogy. Various techniques to improve LID accuracy are also studied. One approach examined is the employment of Vocal Tract Length Normalization to reduce the speech variation caused by di®erent speakers. A linear data fusion technique is adopted to combine the various aspects of information extracted from speech. As a result of this research, a LID system was implemented and presented for evaluation in the 2003 Language Recognition Evaluation conducted by the NIST.

Structural health monitoring in Australia

Structural Health Monitoring (SHM) is defined as the use of on-structure sensing system to monitor the performance of the structure and evaluate its health state. Recent bridge failures, such as the collapses of the 1-35W Highway Bridge in USA, the collapse of the Can Tho Bridge in Vietnam and the Xijiang River Bridge in the Mainland China, all of which happened in the year 2007, have alerted the importance of structural health monitoring. This book presents a background of SHM technologies together with its latest development and successful applications. It is a book launched to celebrate the establishment of the Australian Network of Structural Health Monitoring (ANSHM). The network comprising leading SHM experts in Australia promotes and advances SHM research, application, education and development in Australia.

Structural health monitoring for long span bridges : Hong Kong experience and continuing onto Australia

Structural health monitoring has been accepted as a justified effort for long-span bridges, which are critical to a region's economic vitality. As the most heavily instrumented bridge project in the world, WASHMS - Wind And Structural Health Monitoring System has been developed and installed on the cable-supported bridges in Hong Kong (Wong and Ni 2009a). This chapter aims to share some of the experience gained through the operations and studies on the application of WASHMS. It is concluded that Structural Health Monitoring should be composed of two main components: Structural Performance Monitoring (SPM) and Structural Safety Evaluation (SSE). As an example to illustrate how the WASHMS could be used for structural performance monitoring, the layout of the sensory system installed on the Tsing Ma Bridge is briefly described. To demonstrate the two broad approaches of structural safety evaluation - Structural Health Assessment and Damage Detection, three examples in the application of SHM information are presented. These three examples can be considered as pioneer works for the research and development of the structural diagnosis and prognosis tools required by the structural health monitoring for monitoring and evaluation applications.

Biological monitoring of occupational exposure to polycyclic aromatic hydrocarbons in prebake smelting

In 1984, the International Agency for Research on Cancer determined that working in the primary aluminium production process was associated with exposure to certain polycyclic aromatic hydrocarbons (PAHs) that are probably carcinogenic to humans. Key sources of PAH exposure within the occupational environment of a prebake aluminium smelter are processes associated with use of coal-tar pitch. Despite the potential for exposure via inhalation, ingestion and dermal adsorption, to date occupational exposure limits exist only for airborne contaminants. This study, based at a prebake aluminium smelter in Queensland, Australia, compares exposures of workers who came in contact with PAHs from coal-tar pitch in the smelter’s anode plant (n = 69) and cell-reconstruction area (n = 28), and a non-production control group (n = 17). Literature relevant to PAH exposures in industry and methods of monitoring and assessing occupational hazards associated with these compounds are reviewed, and methods relevant to PAH exposure are discussed in the context of the study site. The study utilises air monitoring of PAHs to quantify exposure via the inhalation route and biological monitoring of 1-hydroxypyrene (1-OHP) in urine of workers to assess total body burden from all routes of entry. Exposures determined for similar exposure groups, sampled over three years, are compared with published occupational PAH exposure limits and/or guidelines. Results of paired personal air monitoring samples and samples collected for 1-OHP in urine monitoring do not correlate. Predictive ability of the benzene-soluble fraction (BSF) in personal air monitoring in relation to the 1-OHP levels in urine is poor (adjusted R2 < 1%) even after adjustment for potential confounders of smoking status and use of personal protective equipment. For static air BSF levels in the anode plant, the median was 0.023 mg/m3 (range 0.002–0.250), almost twice as high as in the cell-reconstruction area (median = 0.013 mg/m3, range 0.003–0.154). In contrast, median BSF personal exposure in the anode plant was 0.036 mg/m3 (range 0.003–0.563), significantly lower than the median measured in the reconstruction area (0.054 mg/m3, range 0.003–0.371) (p = 0.041). The observation that median 1-OHP levels in urine were significantly higher in the anode plant than in the reconstruction area (6.62 µmol/mol creatinine, range 0.09–33.44 and 0.17 µmol/mol creatinine, range 0.001–2.47, respectively) parallels the static air measurements of BSF rather than the personal air monitoring results (p < 0.001). Results of air measurements and biological monitoring show that tasks associated with paste mixing and anode forming in the forming area of the anode plant resulted in higher PAH exposure than tasks in the non-forming areas; median 1-OHP levels in urine from workers in the forming area (14.20 µmol/mol creatinine, range 2.02–33.44) were almost four times higher than those obtained from workers in the non-forming area (4.11 µmol/mol creatinine, range 0.09–26.99; p < 0.001). Results justify use of biological monitoring as an important adjunct to existing measures of PAH exposure in the aluminium industry. Although monitoring of 1-OHP in urine may not be an accurate measure of biological effect on an individual, it is a better indicator of total PAH exposure than BSF in air. In January 2005, interim study results prompted a plant management decision to modify control measures to reduce skin exposure. Comparison of 1-OHP in urine from workers pre- and post-modifications showed substantial downward trends. Exposure via the dermal route was identified as a contributor to overall dose. Reduction in 1-OHP urine concentrations achieved by reducing skin exposure demonstrate the importance of exposure via this alternative pathway. Finally, control measures are recommended to ameliorate risk associated with PAH exposure in the primary aluminium production process, and suggestions for future research include development of methods capable of more specifically monitoring carcinogenic constituents of PAH mixtures, such as benzo[a]pyrene.

Urban growth monitoring techniques for sustainable development

This paper discusses the role of advance techniques for monitoring urban growth and change for sustainable development of urban environment. It also presents results of a case study involving satellite data for land use/land cover classification of Lucknow city using IRS-1C multi-spectral features. Two classification algorithms have been used in the study. Experiments were conducted to see the level of improvement in digital classification of urban environment using Artificial Neural Network (ANN) technique.

An investigation of rail condition monitoring by Fibre Bragg Grating sensors

Condition monitoring on rails and train wheels is vitally important to the railway asset management and the rail-wheel interactions provide the crucial information of the health state of both rails and wheels. Continuous and remote monitoring is always a preference for operators. With a new generation of strain sensing devices in Fibre Bragg Grating (FBG) sensors, this study explores the possibility of continuous monitoring of the health state of the rails; and investigates the required signal processing techniques and their limitations.