61 resultados para Song, Android, Applicazione, Registrazioni Audio.

em Queensland University of Technology - ePrints Archive


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Key Features: "Aligns to Mastering Medical Terminology: Australia and New Zealand. Self-test to practise and revise combining forms, word roots, prefixes and suffixes. Crossword puzzles, anagrams and label-the-diagram exercises Also available iOS/Android app featuring audio glossary, flashcards and MCQs."--publisher website

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Raven and Song Scope are two automated sound anal-ysis tools based on machine learning technique for en-vironmental monitoring. Many research works have been conducted upon them, however, no or rare explo-ration mentions about the performance and comparison between them. This paper investigates the comparisons from six aspects: theory, software interface, ease of use, detection targets, detection accuracy, and potential application. Through deep exploration one critical gap is identified that there is a lack of approach to detect both syllables and call structures, since Raven only aims to detect syllables while Song Scope targets call structures. Therefore, a Timed Probabilistic Automata (TPA) system is proposed which separates syllables first and clusters them into complex structures after.

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This work was commissioned by the Queensland Art Gallery to mark the fifth birthday of the Gallery of Modern Art. The brief was quite open, with the only directive to make the work complement the major exhibition "we miss you magic land!" by Perth artists, Pip & Pop (Tanya Schultz and Nicole Andrijevic). This musical work draws on a similarly otherworldly, childlike theme, influenced in part by the cinematic world of Gene Wilder's Willy Wonka.

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Critical skills such as identifying and appreciating issues that confront firms engaging in international business, and the ability to undertake creative decision-making, are considered fundamental to the study of International Business. It has been argued that using audio-visual case studies can help develop such skills. However, this is difficult due to a lack of Australian case studies. This paper reviews the literature outlining the advantages believed to result from the use of audio-visual case studies, describes a project implemented in a large cohort of students studying International Business, reports on a pilot evaluation of the project, and outlines the findings and conclusions of the survey.

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Acoustically, car cabins are extremely noisy and as a consequence audio-only, in-car voice recognition systems perform poorly. As the visual modality is immune to acoustic noise, using the visual lip information from the driver is seen as a viable strategy in circumventing this problem by using audio visual automatic speech recognition (AVASR). However, implementing AVASR requires a system being able to accurately locate and track the drivers face and lip area in real-time. In this paper we present such an approach using the Viola-Jones algorithm. Using the AVICAR [1] in-car database, we show that the Viola- Jones approach is a suitable method of locating and tracking the driver’s lips despite the visual variability of illumination and head pose for audio-visual speech recognition system.