Bayesian classification of acoustical waveforms under environmental variability

We present in this paper a new multivariate probabilistic approach to Acoustic Pulse Recognition (APR) for tangible interface applications. This model uses Principle Component Analysis (PCA) in a probabilistic framework to classify tapping pulses with a high degree of variability. It was found that this model, achieves a higher robustness to pulse variability than simpler template matching methods, specifically when allowed to train on data containing high variability. © 2011 IEEE.

The environmental and economic sustainability of potential bioethanol from willow in the UK.

Life cycle assessment has been used to investigate the environmental and economic sustainability of a potential operation in the UK in which bioethanol is produced from the hydrolysis and subsequent fermentation of coppice willow. If the willow were grown on idle arable land in the UK, or, indeed, in Eastern Europe and imported as wood chips into the UK, it was found that savings of greenhouse gas emissions of 70-90%, when compared to fossil-derived gasoline on an energy basis, would be possible. The process would be energetically self-sufficient, as the co-products, e.g. lignin and unfermented sugars, could be used to produce the process heat and electricity, with surplus electricity being exported to the National Grid. Despite the environmental benefits, the economic viability is doubtful at present. However, the cost of production could be reduced significantly if the willow were altered by breeding to improve its suitability for hydrolysis and fermentation.

A Bayesian Approach to the Restoration of Degraded Audio Signals

In this paper we derive the a posteriori probability for the location of bursts of noise additively superimposed on a Gaussian AR process. The theory is developed to give a sequentially based restoration algorithm suitable for real-time applications. The algorithm is particularly appropriate for digital audio restoration, where clicks and scratches may be modelled as additive bursts of noise. Experiments are carried out on both real audio data and synthetic AR processes and Significant improvements are demonstrated over existing restoration techniques. © 1995 IEEE

Robust noise reduction for speech and audio signals

Statistical model-based methods are presented for the reconstruction of autocorrelated signals in impulsive plus continuous noise environments. Signals are modelled as autoregressive and noise sources as discrete and continuous mixtures of Gaussians, allowing for robustness in highly impulsive and non-Gaussian environments. Markov Chain Monte Carlo methods are used for reconstruction of the corrupted waveforms within a Bayesian probabilistic framework and results are presented for contaminated voice and audio signals.

Towards a perceptually optimal spectral amplitude estimator for audio signal enhancement

We present a statistical model-based approach to signal enhancement in the case of additive broadband noise. Because broadband noise is localised in neither time nor frequency, its removal is one of the most pervasive and difficult signal enhancement tasks. In order to improve perceived signal quality, we take advantage of human perception and define a best estimate of the original signal in terms of a cost function incorporating perceptual optimality criteria. We derive the resultant signal estimator and implement it in a short-time spectral attenuation framework. Audio examples, references, and further information may be found at http://www-sigproc.eng.cam.ac.uk/~pjw47.

Environmental evaluation of localising production as a strategy for sustainable development: a case study of two consumer goods in Jamaica

The objective of this study was to compare the life-cycle environmental impacts of changed production structures for two consumer goods (high-density polyethylene (HDPE) shopping bags and beds) in Jamaica. A scenario technique was used to construct three alternative production structures for each product; each scenario reflecting an increase in local production in Jamaica which depended on an increased supply of input materials which may be sourced: (1) externally from overseas suppliers, (2) from post-consumer recycling, and (3) locally on the island of Jamaica. These three constructed scenarios were then compared to the existing supply chain or reference scenarios of the products. The results showed that for both case products the recycling scenario was most preferable for localising production, resulting in the lowest environmental impact. This was because the production of raw materials accounted for the largest effect on total environmental impact. As such, the most immediate environmental improvements were realised by lowering the production of virgin materials. © 2007 Elsevier Ltd. All rights reserved.