Joachim Ganseman

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In this work, we investigate a method for score-informed source separation using Probabilistic Latent Component Analysis (PLCA). We present extensive test results that give an indication of the performance of the method, its strengths and weaknesses. For this purpose, we created a test database that has been made available to the public, in order to(More)
Probabilistic Latent Component Analysis is a widely adopted variant of Nonnegative Matrix Factorization for the purpose of single channel audio source separation. It has seen many extensions, including incorporation of prior information derived from music scores. Recent work on the invertibility of the Constant-Q Tranform make that a viable alternative to(More)
The short-time Fourier transform (STFT) based spectrogram is commonly used to analyze the time-frequency content of a signal. Depending on window size, the STFT provides a trade-off between time and frequency resolutions. This paper presents a novel method that achieves high resolution simultaneously in both time and frequency. We extend Probabilistic(More)
MusicXML is a fairly recent XML-based file format for music scores, now supported by many score and audio editing software applications. Several online score library projects exist or are emerging, some of them using MusicXML as main format. When storing a large set of XML-encoded scores in an XML database, XQuery can be used to retrieve information from(More)
In this paper we present fast and scalable methods to access relevant data from music scores stored in an XML based notation format, with the explicit goal of using scores in real-time audio processing frameworks. Quick and easy access is important when accessing or traversing a score, for instance for real-time playback. Any time complexity improvement in(More)
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