Transcription of multi-genre media archives using out-of-domain data

We describe our work on developing a speech recognition system for multi-genre media archives. The high diversity of the data makes this a challenging recognition task, which may benefit from systems trained on a combination of in-domain and out-of-domain data. Working with tandem HMMs, we present Multi-level Adaptive Networks (MLAN), a novel technique for incorporating information from out-of-domain posterior features using deep neural networks. We show that it provides a substantial reduction in WER over other systems, with relative WER reductions of 15% over a PLP baseline, 9% over in-domain tandem features and 8% over the best out-of-domain tandem features. © 2012 IEEE.

In vitro recording of neural activity using carbon nanosheet microelectrodes

The advent of nanotechnology has revolutionised our ability to engineer electrode interfaces. These are particularly attractive to measure biopotentials, and to study the nervous system. In this work, we demonstrate enhanced in vitro recording of neuronal activity using electrodes decorated with carbon nanosheets (CNSs). This material comprises of vertically aligned, free standing conductive sheets of only a few graphene layers with a high surfacearea- to-volume ratio, which makes them an interesting material for biomedical electrodes. Further, compared to carbon nanotubes, CNSs can be synthesised without the need for metallic catalysts like Ni, Co or Fe, thereby reducing potential cytotoxicity risks. Electrochemical measurements show a five times higher charge storage capacity, and an almost ten times higher double layer capacitance as compared to TiN. In vitro experiments were performed by culturing primary hippocampal neurons from mice on micropatterned electrodes. Neurophysiological recordings exhibited high signal-to-noise ratios of 6.4, which is a twofold improvement over standard TiN electrodes under the same conditions. © 2013 Elsevier Ltd. All rights reserved.

Characterization and deformation response of orthotropic fibre networks with auxetic out-of-plane behaviour

In the present paper, highly porous fibre networks made of 316L fibres, with different fibre volume fractions, are characterized in terms of network architecture, elastic constants and fracture energies. Elastic constants are measured using quasi-static mechanical and modal vibration testing, yielding local and globally averaged properties, respectively. Differences between quasi-static and dynamic elastic constants are attributed to through-thickness shear effects. Regardless of the method employed, networks show signs of material inhomogeneity at high fibre densities, in agreement with X-ray nanotomography results. Strong auxetic (or negative Poisson's ratio) behaviour is observed in the through-thickness direction, which is attributed to fibre kinking induced during processing. Measured fracture energies are compared with model predictions incorporating information about in-plane fibre orientation distribution, fibre volume fraction and single fibre work of fracture. Experimental values are broadly consistent with model predictions, based on the assumption that this energy is primarily associated with plastic deformation of individual fibres within a process zone of the same order as the inter-joint spacing. © 2013 Published by Elsevier Ltd. on behalf of Acta Materialia Inc. All rights reserved.