Speech recognition using ad-hoc microphone arrays

While close talking microphones give the best signal quality and produce the highest accuracy from current Automatic Speech Recognition (ASR) systems, the speech signal enhanced by microphone array has been shown to be an effective alternative in a noisy environment. The use of microphone arrays in contrast to close talking microphones alleviates the feeling of discomfort and distraction to the user. For this reason, microphone arrays are popular and have been used in a wide range of applications such as teleconferencing, hearing aids, speaker tracking, and as the front-end to speech recognition systems. With advances in sensor and sensor network technology, there is considerable potential for applications that employ ad-hoc networks of microphone-equipped devices collaboratively as a virtual microphone array. By allowing such devices to be distributed throughout the users’ environment, the microphone positions are no longer constrained to traditional fixed geometrical arrangements. This flexibility in the means of data acquisition allows different audio scenes to be captured to give a complete picture of the working environment. In such ad-hoc deployment of microphone sensors, however, the lack of information about the location of devices and active speakers poses technical challenges for array signal processing algorithms which must be addressed to allow deployment in real-world applications. While not an ad-hoc sensor network, conditions approaching this have in effect been imposed in recent National Institute of Standards and Technology (NIST) ASR evaluations on distant microphone recordings of meetings. The NIST evaluation data comes from multiple sites, each with different and often loosely specified distant microphone configurations. This research investigates how microphone array methods can be applied for ad-hoc microphone arrays. A particular focus is on devising methods that are robust to unknown microphone placements in order to improve the overall speech quality and recognition performance provided by the beamforming algorithms. In ad-hoc situations, microphone positions and likely source locations are not known and beamforming must be achieved blindly. There are two general approaches that can be employed to blindly estimate the steering vector for beamforming. The first is direct estimation without regard to the microphone and source locations. An alternative approach is instead to first determine the unknown microphone positions through array calibration methods and then to use the traditional geometrical formulation for the steering vector. Following these two major approaches investigated in this thesis, a novel clustered approach which includes clustering the microphones and selecting the clusters based on their proximity to the speaker is proposed. Novel experiments are conducted to demonstrate that the proposed method to automatically select clusters of microphones (ie, a subarray), closely located both to each other and to the desired speech source, may in fact provide a more robust speech enhancement and recognition than the full array could.

Researching crime and violence: Untold stories from the field

Undertaking empirical research on crime and violence can be a tricky enterprise fraught with ethical, methodological, intellectual and legal implications. This chapter takes readers on a reflective journey through the qualitative methodologies I used to research sex work in Kings Cross, miscarriages of justice, female delinquency, sexual violence, and violence in rural and regional settings over a period of nearly 30 years. Reflecting on these experiences, the chapter explores and analyses the reality of doing qualitative field research, the role of the researcher, the politics of subjectivity, the exercise of power, and the ‘muddiness’ of the research process, which is often overlooked in sanitised accounts of the research process (Byrne-Armstrong, Higgs and Horsfall, 2001; Davies, 2000).

Examination of pencil beam predictions of small-field dose using dosimetry film and Monte Carlo simulations

The iPlan treatment planning sys-tem uses a pencil beam algorithm, with density cor-rections, to predict the doses delivered by very small (stereotactic) radiotherapy fields. This study tests the accuracy of dose predictions made by iPlan, for small-field treatments delivered to a planar solid wa-ter phantom and to heterogeneous human tissue using the BrainLAB m3 micro-multileaf collimator.

Component reliability estimations without field data

Maintenance activities in a large-scale engineering system are usually scheduled according to the lifetimes of various components in order to ensure the overall reliability of the system. Lifetimes of components can be deduced by the corresponding probability distributions with parameters estimated from past failure data. While failure data of the components is not always readily available, the engineers have to be content with the primitive information from the manufacturers only, such as the mean and standard deviation of lifetime, to plan for the maintenance activities. In this paper, the moment-based piecewise polynomial model (MPPM) are proposed to estimate the parameters of the reliability probability distribution of the products when only the mean and standard deviation of the product lifetime are known. This method employs a group of polynomial functions to estimate the two parameters of the Weibull Distribution according to the mathematical relationship between the shape parameter of two-parameters Weibull Distribution and the ratio of mean and standard deviation. Tests are carried out to evaluate the validity and accuracy of the proposed methods with discussions on its suitability of applications. The proposed method is particularly useful for reliability-critical systems, such as railway and power systems, in which the maintenance activities are scheduled according to the expected lifetimes of the system components.

Mild systemic hypoxia and photopic visual field sensitivity

Purpose: Flickering stimuli increase the metabolic demand of the retina,making it a sensitive perimetric stimulus to the early onset of retinal disease. We determine whether flickering stimuli are a sensitive indicator of vision deficits resulting from to acute, mild systemic hypoxia when compared to standard static perimetry. Methods: Static and flicker visual perimetry were performed in 14 healthy young participants while breathing 12% oxygen (hypoxia) under photopic illumination. The hypoxia visual field data were compared with the field data measured during normoxia. Absolute sensitivities (in dB) were analysed in seven concentric rings at 1°, 3°, 6°, 10°, 15°, 22° and 30° eccentricities as well as mean defect (MD) and pattern defect (PD) were calculated. Preliminary data are reported for mesopic light levels. Results: Under photopic illumination, flicker and static visual field sensitivities at all eccentricities were not significantly different between hypoxia and normoxia conditions. The mean defect and pattern defect were not significantly different for either test between the two oxygenation conditions. Conclusion: Although flicker stimulation increases cellular metabolism, flicker photopic visual field impairment is not detected during mild hypoxia. These findings contrast with electrophysiological flicker tests in young participants that show impairment at photopic illumination during the same levels of mild hypoxia. Potential mechanisms contributing to the difference between the visual fields and electrophysiological flicker tests including variability in perimetric data, neuronal adaptation and vascular autoregulation, are considered. The data have implications for the use of visual perimetry in the detection of ischaemic/hypoxic retinal disorders under photopic and mesopic light levels.