2,482 research outputs found

    Gaussian Framework for Interference Reduction in Live Recordings

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    Here typical live full-length music recordings are considered. In this scenarios, some instrumental voices are captured by microphones intended to other voices, leading to so-called “interferences”. Reducing this phenomenon is desirable because it opens new possibilities for sound engineers and also it has been proven that it increase performances of music analysis and processing tools (e.g. pitch tracking). In this work we propose an fast NMF-based algorithm to solve this problem.ope

    Independent Component Analysis Enhancements for Source Separation in Immersive Audio Environments

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    In immersive audio environments with distributed microphones, Independent Component Analysis (ICA) can be applied to uncover signals from a mixture of other signals and noise, such as in a cocktail party recording. ICA algorithms have been developed for instantaneous source mixtures and convolutional source mixtures. While ICA for instantaneous mixtures works when no delays exist between the signals in each mixture, distributed microphone recordings typically result various delays of the signals over the recorded channels. The convolutive ICA algorithm should account for delays; however, it requires many parameters to be set and often has stability issues. This thesis introduces the Channel Aligned FastICA (CAICA), which requires knowledge of the source distance to each microphone, but does not require knowledge of noise sources. Furthermore, the CAICA is combined with Time Frequency Masking (TFM), yielding even better SOI extraction even in low SNR environments. Simulations were conducted for ranking experiments tested the performance of three algorithms: Weighted Beamforming (WB), CAICA, CAICA with TFM. The Closest Microphone (CM) recording is used as a reference for all three. Statistical analyses on the results demonstrated superior performance for the CAICA with TFM. The algorithms were applied to experimental recordings to support the conclusions of the simulations. These techniques can be deployed in mobile platforms, used in surveillance for capturing human speech and potentially adapted to biomedical fields

    Evaluation of live human-computer music-making: Quantitative and qualitative approaches

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    NOTICE: this is the author’s version of a work that was accepted for publication in International Journal of Human-Computer Studies. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in International Journal of Human-Computer Studies, [VOL 67,ISS 11(2009)] DOI: 10.1016/j.ijhcs.2009.05.00

    Applying source separation to music

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    International audienceSeparation of existing audio into remixable elements is very useful to repurpose music audio. Applications include upmixing video soundtracks to surround sound (e.g. home theater 5.1 systems), facilitating music transcriptions, allowing better mashups and remixes for disk jockeys, and rebalancing sound levels on multiple instruments or voices recorded simultaneously to a single track. In this chapter, we provide an overview of the algorithms and approaches designed to address the challenges and opportunities in music. Where applicable, we also introduce commonalities and links to source separation for video soundtracks, since many musical scenarios involve video soundtracks (e.g. YouTube recordings of live concerts, movie sound tracks). While space prohibits describing every method in detail, we include detail on representative music‐specific algorithms and approaches not covered in other chapters. The intent is to give the reader a high‐level understanding of the workings of key exemplars of the source separation approaches applied in this domain

    The IceCube Neutrino Observatory: Instrumentation and Online Systems

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    The IceCube Neutrino Observatory is a cubic-kilometer-scale high-energy neutrino detector built into the ice at the South Pole. Construction of IceCube, the largest neutrino detector built to date, was completed in 2011 and enabled the discovery of high-energy astrophysical neutrinos. We describe here the design, production, and calibration of the IceCube digital optical module (DOM), the cable systems, computing hardware, and our methodology for drilling and deployment. We also describe the online triggering and data filtering systems that select candidate neutrino and cosmic ray events for analysis. Due to a rigorous pre-deployment protocol, 98.4% of the DOMs in the deep ice are operating and collecting data. IceCube routinely achieves a detector uptime of 99% by emphasizing software stability and monitoring. Detector operations have been stable since construction was completed, and the detector is expected to operate at least until the end of the next decade.Comment: 83 pages, 50 figures; updated with minor changes from journal review and proofin

    Roadmap on digital holography [Invited]

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    This Roadmap article on digital holography provides an overview of a vast array of research activities in the field of digital holography. The paper consists of a series of 25 sections from the prominent experts in digital holography presenting various aspects of the field on sensing, 3D imaging and displays, virtual and augmented reality, microscopy, cell identification, tomography, label-free live cell imaging, and other applications. Each section represents the vision of its author to describe the significant progress, potential impact, important developments, and challenging issues in the field of digital holography
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