The Convergence Review and the future of Australian content regulation

This article examines the place of Australian and local content regulation in the new media policy framework proposed by the Convergence Review. It outlines the history of Australian content regulation and the existing policy framework, before going on to detail some of the debates around Australian content during the Review. The final section analyses the relevant recommendations in the Convergence Review Final Report, and highlights some issues and problems that may arise in the new framework

Platonov revisited: past and present views on the land of the philosophers

The current article highlights the most important moments in the disclosure of Platonov’s oeuvre and in the evolution of its scholarly study since the writer’s death in 1951. Special attention is paid to the major tendencies in Platonov scholarship – the predominance of politicized readings from the mid-1960s until the late perestroika era, a certain deideologization and an increased interest in philosophical and mythopoetical topics since the late 1980s, and a growing interest for the cultural and historical context(s) of Platonov’s oeuvre today. The article also serves as an introduction to the special issue of Russian Literature devoted to the changes in the scholarly study of Platonov’s oeuvre

Approximations of strongly continuous families of unbounded self-adjoint operators

The problem of approximating the discrete spectra of families of self-adjoint operators that are merely strongly continuous is addressed. It is well-known that the spectrum need not vary continuously (as a set) under strong perturbations. However, it is shown that under an additional compactness assumption the spectrum does vary continuously, and a family of symmetric finite-dimensional approximations is constructed. An important feature of these approximations is that they are valid for the entire family uniformly. An application of this result to the study of plasma instabilities is illustrated.Comment: 22 pages, final version to appear in Commun. Math. Phy

Reconstructing intelligible audio speech from visual speech features

This work describes an investigation into the feasibility of producing intelligible audio speech from only visual speech fea- tures. The proposed method aims to estimate a spectral enve- lope from visual features which is then combined with an arti- ficial excitation signal and used within a model of speech pro- duction to reconstruct an audio signal. Different combinations of audio and visual features are considered, along with both a statistical method of estimation and a deep neural network. The intelligibility of the reconstructed audio speech is measured by human listeners, and then compared to the intelligibility of the video signal only and when combined with the reconstructed audio

Voicing classification of visual speech using convolutional neural networks

The application of neural network and convolutional neural net- work (CNN) architectures is explored for the tasks of voicing classification (classifying frames as being either non-speech, unvoiced, or voiced) and voice activity detection (VAD) of vi- sual speech. Experiments are conducted for both speaker de- pendent and speaker independent scenarios. A Gaussian mixture model (GMM) baseline system is de- veloped using standard image-based two-dimensional discrete cosine transform (2D-DCT) visual speech features, achieving speaker dependent accuracies of 79% and 94%, for voicing classification and VAD respectively. Additionally, a single- layer neural network system trained using the same visual fea- tures achieves accuracies of 86 % and 97 %. A novel technique using convolutional neural networks for visual speech feature extraction and classification is presented. The voicing classifi- cation and VAD results using the system are further improved to 88 % and 98 % respectively. The speaker independent results show the neural network system to outperform both the GMM and CNN systems, achiev- ing accuracies of 63 % for voicing classification, and 79 % for voice activity detection

The Environmental Porter Hypothesis as a Technology Adoption Problem?

The Porter Hypothesis postulates that the costs of compliance with environmental standards may be partially or even fully offset by adoption of innovations they trigger. The timing of the adoption aspect of the Porter Hypothesis has not been captured in formal theory so far. We show in this paper how the Porter Hypothesis can be approached using a model of technology adoption. In the Reinganum-Fudenberg-Tirole game of timing, a firm adopts earlier under stricter environmental taxation, and under some circumstances can credibly precommit to early adoption. We show that all times of adoption - preemption, following and joint late adoption - are earlier the higher the non-adoption tax. Under preemption the firm of the country that varies environmental taxes will adopt first with certainty indicating increased competitiveness, but get lower profits than without environ- mental policy. Thus the Porter Hypothesis of increasing overall profits is rejected.economics of technology ;