The high road or the low road? Alternatives for Australia's future

The OECD suggests that countries now have a choice. They can focus on development based on either:  competition via investment in technology and innovation - which is important in high knowledge industries and high innovation economies, or  competition via exchange rates and wages - which is important in industries producing standardised, lower-tech goods and services. The first route will maximise higher-skilled, higher-paid employment growth and living standards. Given the lack of control over the exchange rate, the second route requires competition based on wages. It is essential to understand that markets themselves won’t shift a country from one path to the other. These conclusions arise from the OECD’s recognition that technical progress - the creation of new products or the adoption of more efficient methods of production - is the main source of economic growth and enhanced quality of life. Technological change is, the OECD suggests, ...also the engine for job creation as higher wages and profits resulting from technology-induced productivity gains and lower prices lead to increased demand for new products from existing as well as new industries (1997: 4).Further, Competitiveness in high-technology industries is mainly driven by technology factors and much less by wage and exchange rate movements, while the reverse is true in low-technology industries (OECD 1996e: 12). The OECD has shown that sound macroeconomic conditions, such as the low inflation and reduced public sector debt visible in almost all member countries in the 1990s, are not enough to deal with high levels of unemployment and the need to increase levels of income: If economic performance is to improve, additional structural reform, which can increase innovation and the diffusion of technologies within and among national economies, seems necessary (OECD 1997: 4 Emphasis added).

Summary report : the high road or the low road? Alternatives for Australia's future

This document is a summary of the findings of the inaugural study commissioned by the Australian Business Foundation Limited. It was conducted by Professor Jane Marceau, Pro-Vice Chancellor (Research) at the University of Western Sydney Macarthur, Dr Karen Manley, Visiting Research Fellow at the University of Western Sydney Macarthur and Mr Derek Sicklen, Managing Director of Australian Economic Analysis Pty Limited. The full report is available from the Australian Business Foundation. The Australian Business Foundation Limited is a recently formed independent economic and industry policy think-tank. It has been established and sponsored by Australian Business Limited, a pre-eminent and long-standing industry association and business services network. The report is in three parts. The first reviews the key findings of contemporary international economic and innovation-oriented analyses of the characteristics of high growth economies. The second assesses the shape, structure and dynamics of Australian industry as these compare with the characteristics for successful economic development suggested in the literature. Finally, the report indicates the nature of urgently required policy directions.

Speaker identification using higher order spectral phase features and their effectiveness vis-a-vis Mel-Cepstral features

The effectiveness of higher-order spectral (HOS) phase features in speaker recognition is investigated by comparison with Mel Cepstral features on the same speech data. HOS phase features retain phase information from the Fourier spectrum unlikeMel–frequency Cepstral coefficients (MFCC). Gaussian mixture models are constructed from Mel– Cepstral features and HOS features, respectively, for the same data from various speakers in the Switchboard telephone Speech Corpus. Feature clusters, model parameters and classification performance are analyzed. HOS phase features on their own provide a correct identification rate of about 97% on the chosen subset of the corpus. This is the same level of accuracy as provided by MFCCs. Cluster plots and model parameters are compared to show that HOS phase features can provide complementary information to better discriminate between speakers.