In this paper we present preliminary results obtained at Dragon Systems on the Resource Maaaagernent benchmark task. The basic conceptual units of our system are Phonemes-m-Context (PICs), which are represented as Hidden Mmkov Models, each of which is eapressed as a sequence of Phonetic Elements (PELs). The PELs corresponding to a given phoneme constitute a kind of alphabet for the representation of PICs.For the speaker-dependent tests, two basic methods of training the acoustic models were investigated. 'nac first method of training the Resouro~ Managemera models is to ~e-estimate the models for each test speaker from that speaker's training data, keeping the PEL spellings of the PICs fixed. The second approach is to use the re-estimated models from the first melhod to derive a segmentation of the training data, then to respall the PICs in a hrgely speaker-depmdmt manner in order to improve the representation of speaker differences. A full explanation of these methods is given, as are results using each method.In addition to repotting on two different training slrategies, we disoass NBest results. The N-Best algorithm is a modification of the algorithm proposed by Soong and Huang at the Jtme 1990 workshop. This algorithm runs as a post-processing step and uses an A*-search (an algorithm also known as a 'stack decoder').
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This research investigates models for engaging private sector investors and developers in financing or delivering social and affordable housing, across different market segments and tenures in Australia and internationally. It also identifies key existing and potential players, and financial, regulatory, or development barriers to wider participation.Prior to the COVID-19 pandemic, around 3,000 social and affordable dwellings were being produced per year, against an estimated annual need of around 36,000 homes. To meet the forecast demand, it is clear ‘hybridity’ of the housing system is essential, whereby social and affordable housing is increasingly financed, developed and managed by a combination of government, community-based and market providers, and cross-sector partnerships; no one sector can address the need alone. This study highlighted that a range of established and emerging affordable housing product types can be supported through collaboration with private not-for-profit and for-profit partners. These strategies include public private partnerships, mixed tenure developments, tax subsidies for affordable supply, home ownership schemes, build to rent and inclusionary planning mechanisms. These depend on different combinations of government subsidy, policy settings, and regulation, and are suitable for delivery across a variety of different development contexts.
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