Justin Lundberg

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In this paper we propose a real-time signal processing framework for musical audio that 1) aligns the audio with an existing music score or creates a musical score by automated music transcription algorithms; and 2) obtains the expressive feature descriptors of music performance by comparing the score with the audio. Real-time audio segmentation algorithms(More)
In previous immunohistochemical studies, chronic venous insufficiency (CVI) ulcers have been shown to display positive staining for interleukin-10 (IL-10), while other wounds (including autologous donor wound tissue) show a reduced staining level. IL-10 inhibits the synthesis of many proinflammatory cytokines, while also inhibiting antigen presentation by(More)
We present a framework to provide a quantitative representation of aspects of musical sound that are associated with musical expressiveness and emotions. After a brief introduction to the background of expressive features in music, we introduce a score to audio mapping algorithm based on dynamic time warping, which segments the audio by comparing it to a(More)
We propose generative modeling algorithms that analyze the temporal features of non-stationary signals and represent their temporal structural dependencies using hierarchical probabilistic graphical models. First, several template sampling methods are introduced to embed the temporal signal features into multiple instantiations of statistical variables.(More)
In this paper we present a transcription method for polyphonic music. The short time Fourier transform is used first to decompose an acoustic signal into sonic partials in a time-frequency representation. In general the segmented partials exhibit distinguishable features if they originate from different “voices” in the polyphonic mix. We(More)
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