Raw Multi-Channel Audio Source Separation using Multi-Resolution Convolutional Auto-Encoders

Supervised multi-channel audio source separation requires extracting useful spectral, temporal, and spatial features from the mixed signals. The success of many existing systems is therefore largely dependent on the choice of features used for training. In this work, we introduce a novel multi-channel, multi-resolution convolutional auto-encoder neural network that works on raw time-domain signals to determine appropriate multi-resolution features for separating the singing-voice from stereo music. Our experimental results show that the proposed method can achieve multi-channel audio source separation without the need for hand-crafted features or any pre- or post-processing

Multi-Resolution Fully Convolutional Neural Networks for Monaural Audio Source Separation

In deep neural networks with convolutional layers, each layer typically has fixed-size/single-resolution receptive field (RF). Convolutional layers with a large RF capture global information from the input features, while layers with small RF size capture local details with high resolution from the input features. In this work, we introduce novel deep multi-resolution fully convolutional neural networks (MR-FCNN), where each layer has different RF sizes to extract multi-resolution features that capture the global and local details information from its input features. The proposed MR-FCNN is applied to separate a target audio source from a mixture of many audio sources. Experimental results show that using MR-FCNN improves the performance compared to feedforward deep neural networks (DNNs) and single resolution deep fully convolutional neural networks (FCNNs) on the audio source separation problem.Comment: arXiv admin note: text overlap with arXiv:1703.0801

Exit velocity: the media election

The previous campaign of 2010 produced electoral firsts in media terms (the televised leaders' debates), drama and unpredictability (‘Cleggmania’) and memorable moments (Gordon Brown's ‘bigoted woman’ comments) all of which disrupted the parties' planned scripts. Arguably, the 2015 election seems to have been its very antithesis. The plodding six-week campaign has been widely been portrayed as dull, stage-managed, narrowly focused and lacking in surprise moments, but with a dramatic ending on election night, as the broadcasters announced the shock exit poll. The disbelieving former Liberal Democrat leader Paddy Ashdown declared ‘he would eat his hat’ if his party suffered the losses predicted by the forecast; in fact the result was even worse. Ashdown like so many of his fellow commentators, whether of the traditional offline or online media varieties, was stunned by the apparent failure of the opinion polls to foresee the Conservative victory. What followed was the political equivalent of ‘exit velocity’ in the aftermath of a plodding election, with frenetic, intensive debate over the future of the UK sparking the kind of passion lacking in the preceding campaign. The 2015 campaign as reported in the media was predicated on the assumption that the outcome would be another hung Parliament and, possibly, coalition government. This was constantly reinforced by a stream of experts and opinion-formers fixated on what might happen after the election rather what had just happened in the previous Parliament. This augmented the potential power-broking role of emerging ‘challengers’ such as UKIP, the SNP and Greens at the marked expense of the Liberal Democrats, clear beneficiaries of the added exposure they had received in 2010. Yet if the campaign differed in terms of its focus on these growing political parties it was also reminiscent of the previous one with its similar emphasis on polls and other aspects

Applications of loudness models in audio engineering

This thesis investigates the application of perceptual models to areas of audio engineering, with a particular focus on music production. The goal was to establish efficient and practical tools for the measurement and control of the perceived loudness of musical sounds. Two types of loudness model were investigated: the single-band model and the multiband excitation pattern (EP) model. The heuristic single-band devices were designed to be simple but sufficiently effective for real-world application, whereas the multiband procedures were developed to give a reasonable account of a large body of psychoacoustic findings according to a functional model of the peripheral hearing system. The research addresses the extent to which current models of loudness generalise to musical instruments, and whether can they be successfully employed in music applications. The domain-specific disparity between the two types of model was first tackled by reducing the computational load of state-of-the-art EP models to allow for fast but low-error auditory signal processing. Two elaborate hearing models were analysed and optimised using musical instruments and speech as test stimuli. It was shown that, after significantly reducing the complexity of both procedures, estimates of global loudness, such as peak loudness, as well as the intermediate auditory representations can be preserved with high accuracy. Based on the optimisations, two real-time applications were developed: a binaural loudness meter and an automatic multitrack mixer. This second system was designed to work independently of the loudness measurement procedure, and therefore supports both linear and nonlinear models. This allowed for a single mixing device to be assessed using different loudness metrics and this was demonstrated by evaluating three configurations through subjective assessment. Unexpectedly, when asked to rate both the overall quality of a mix and the degree to which instruments were equally loud, listeners preferred mixes generated using heuristic single-band models over those produced using a multiband procedure. A series of more systematic listening tests were conducted to further investigate this finding. Subjective loudness matches of musical instruments commonly found in western popular music were collected to evaluate the performance of five published models. The results were in accord with the application-based assessment, namely that current EP procedures do not generalise well when estimating the relative loudness of musical sounds which have marked differences in spectral content. Model specific issues were identified relating to the calculation of spectral loudness summation (SLS) and the method used to determine the global-loudness percept of time-varying musical sounds; associated refinements were proposed. It was shown that a new multiband loudness model with a heuristic loudness transformation yields superior performance over existing methods. This supports the idea that a revised model of SLS is needed, and therefore that modification to this stage in existing psychoacoustic procedures is an essential step towards the goal of achieving real-world deployment

Level of protein kinase C activity correlates directly with resistance to adriamycin in murine fibrosarcoma cells

AbstractIn this report, we demonstrate a direct correlation between protein kinase C (PKC) activity and adriamycin (ADR) resistance in mouse fibrosarcoma cells. PKC activity was measured in four murine UV-2237M fibrosarcoma cell lines that differed in the degrees to which they expressed resistance to ADR, which is an inhibitor of PKC. A comparison of the four cell lines revealed a positive correlation between the level of PKC activity and resistance to ADR. Incubation of the cells with the PKC inhibitor H-7 produced a partial reversal of ADR resistance. Taken together, these results suggest a role for PKC in the mechanism of ADR resistance

Analysing multi-person timing in music and movement : event based methods

Accurate timing of movement in the hundreds of milliseconds range is a hallmark of human activities such as music and dance. Its study requires accurate measurement of the times of events (often called responses) based on the movement or acoustic record. This chapter provides a comprehensive over - view of methods developed to capture, process, analyse, and model individual and group timing [...] This chapter is structured in five main sections, as follows. We start with a review of data capture methods, working, in turn, through a low cost system to research simple tapping, complex movements, use of video, inertial measurement units, and dedicated sensorimotor synchronisation software. This is followed by a section on music performance, which includes topics on the selection of music materials, sound recording, and system latency. The identification of events in the data stream can be challenging and this topic is treated in the next section, first for movement then for music. Finally, we cover methods of analysis, including alignment of the channels, computation of between channel asynchrony errors and modelling of the data set

Timescale analysis of a mathematical model of acetaminophen metabolism and toxicity

Acetaminophen is a widespread and commonly used painkiller all over the world. However, it can cause liver damage when taken in large doses or at repeated chronic doses. Current models of acetaminophen metabolism are complex, and limited to numerical investigation though provide results that represent clinical investigation well. We derive a mathematical model based on mass action laws aimed at capturing the main dynamics of acetaminophen metabolism, in particular the contrast between normal and overdose cases, whilst remaining simple enough for detailed mathematical analysis that can identify key parameters and quantify their role in liver toxicity. We use singular perturbation analysis to separate the different timescales describing the sequence of events in acetaminophen metabolism, systematically identifying which parameters dominate during each of the successive stages. Using this approach we determined, in terms of the model parameters, the critical dose between safe and overdose cases, timescales for exhaustion and regeneration of important cofactors for acetaminophen metabolism and total toxin accumulation as a fraction of initial dose

Latent regulatory potential of human-specific repetitive elements

At least half of the human genome is derived from repetitive elements, which are often lineage specific and silenced by a variety of genetic and epigenetic mechanisms. Using a transchromosomic mouse strain that transmits an almost complete single copy of human chromosome 21 via the female germline, we show that a heterologous regulatory environment can transcriptionally activate transposon-derived human regulatory regions. In the mouse nucleus, hundreds of locations on human chromosome 21 newly associate with activating histone modifications in both somatic and germline tissues, and influence the gene expression of nearby transcripts. These regions are enriched with primate and human lineage-specific transposable elements, and their activation corresponds to changes in DNA methylation at CpG dinucleotides. This study reveals the latent regulatory potential of the repetitive human genome and illustrates the species specificity of mechanisms that control it