298 resultados para Spatial Audio

em Queensland University of Technology - ePrints Archive


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‘Dark Cartographies’ is a slowly evolving meditation upon seasonal change, life after light and the occluding shadows of human influence. Through creating experiences of the many ‘times of a night’ the work allows participants to experience deep engagement with rich spectras of hidden place and sound. By amplifying and shining light upon a myriad of lives lived in blackness, ‘Dark Cartographies’ tempts us to re-understand seasonal change as actively-embodied temporality, inflected by our climate-changing disturbances. ‘Dark Cartographies’ uses custom interactive systems, illusionary techniques and real time spatial audio that draw upon a rich array of media, including seasonal, nocturnal field recordings sourced in the Far North Queensland region and detailed observations of foliage & flowering phases. By drawing inspiration from the subtle transitions between what Europeans named ‘Summer’ and ‘Autumn’, and by including the body and its temporal disturbances within the work, ‘Dark Cartographies’ creates compellingly immersive environments that wrap us in atmospheres beyond sight and hearing. ‘Dark Cartographies’ is a dynamic new installation directed & choreographed by environmental cycles; alluding to a new framework for making works that we call ‘Seasonal’. This powerful, responsive & experiential work draws attention to that which will disappear when biodiverse worlds have descended into an era of permanent darkness – an ‘extinction of human experience’. By tapping into the deeply interlocking seasonal cycles of environments that are themselves intimately linked with social, geographical & political concerns, participating audiences are therefore challenged to see the night, their locality & ecologies in new ways through extending their personal limits of perception, imagery & comprehension.

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An evolving meditation upon the complex, periodic processes that mark Australia’s seasonality, and our increasing ability to disturb them. By amplifying and shining light upon a myriad of mysterious lives lived in blackness, the work presents a sensuous, deep engagement with the rich, irregular spectras of seasonal forms: whilst hinting at a far less comforting background increasingly framed by anthropogenic climate change. ’Temporal’ uses custom interactive systems, illusionary techniques and real time spatial audio processes that draw upon a rich array of media, including seasonal, nocturnal field recordings sourced in the Bundaberg region and detailed observations of foliage & flowering phases from that region. By drawing inspiration from the subtle transitions between what Europeans once named ‘Summer’ and ‘Autumn’ and the multiple seasons recognised by other cultures, whilst also including bodily disturbances within the work, ’Temporal’ creates a compellingly immersive environment that wraps audiences in luscious yet ominous atmospheres beyond sight and hearing. This work completes a two year long project of dynamic mediated installations that have been presented in Sydney, Beijing, Cairns and Bundanon, that have each been somehow choreographed by environmental cycles; alluding to a new framework for making works that we named ‘Seasonal’. These powerful, responsive & experiential works each draw attention to that which will disappear when biodiverse worlds have descended into an era of permanent darkness – an ‘extinction of human experience’. By tapping into the deeply interlocking seasonal cycles of environments that are themselves intimately linked with social, geographical & political concerns, participating audiences are therefore challenged to see the night, their locality & ecologies in new ways through extending their personal limits of perception, imagery & comprehension.

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Automated digital recordings are useful for large-scale temporal and spatial environmental monitoring. An important research effort has been the automated classification of calling bird species. In this paper we examine a related task, retrieval of birdcalls from a database of audio recordings, similar to a user supplied query call. Such a retrieval task can sometimes be more useful than an automated classifier. We compare three approaches to similarity-based birdcall retrieval using spectral ridge features and two kinds of gradient features, structure tensor and the histogram of oriented gradients. The retrieval accuracy of our spectral ridge method is 94% compared to 82% for the structure tensor method and 90% for the histogram of gradients method. Additionally, this approach potentially offers a more compact representation and is more computationally efficient.