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  • Audio source separation with deep neural networks using the dropout algorithm

    Zermini, Alfredo; Wang, Wenwu; Kong, Qiuqiang; Xu, Yong; Plumbley, Mark (2017)
    A method based on Deep Neural Networks (DNNs) and time-frequency masking has been recently developed for binaural audio source separation. In this method, the DNNs are used to predict the Direction Of Arrival (DOA) of the audio sources with respect to the listener which is then used to generate soft time-frequency masks for the recovery/estimation of the individual audio sources. In this paper, an algorithm called ‘dropout’ will be applied to the hidden layers, affecting ...

    Damocles and the Plucked: Audience Participation and Risk in Half Cut

    Alston, A (2012)
    This article looks to identify a political mode of audience engagement in the ‘one-on-one’ performance, Half Cut. In response to recent economic turbulence in the UK and abroad, I draw on Hans-Thies Lehmann’s appeal for an ‘aesthetics of risk’ in the theatre: an aesthetics which I suggest might begin at the level of audience reception. This marks a turn away from the more prevalent application of risk to artistic production. Couched in the sociological context of Ulrich Beck’s ‘risk society’,...

    Integrating corpus work into secondary education: From data-driven learning to needs- …

    Braun, S (2007)
    This paper reports on an empirical case study conducted to investigate the overall conditions and challenges of integrating corpus materials and corpus-based learning activities into Englishlanguage classes at a secondary school in Germany. Starting from the observation that in spite of the large amount of research into corpus-based language learning, hands-on work with corpora has remained an exception in secondary schools, the paper starts by outlining a set of pedagogical requirements for ...

    A visual voice activity detection method with adaboosting

    Liu, Q; Wang, W; Jackson, PJB (2011)
    Spontaneous speech in videos capturing the speaker's mouth provides bimodal information. Exploiting the relationship between the audio and visual streams, we propose a new visual voice activity detection (VAD) algorithm, to overcome the vulnerability of conventional audio VAD techniques in the presence of background interference. First, a novel lip extraction algorithm combining rotational templates and prior shape constraints with active contours is introduced. The visual features are then o...
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