Samer A. Abdallah

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Note onset detection and localization is useful in a number of analysis and indexing techniques for musical signals. The usual way to detect onsets is to look for "transient" regions in the signal, a notion that leads to many definitions: a sudden burst of energy, a change in the short-time spectrum of the signal or in the statistical properties, etc. The(More)
In this paper we propose a text represention for musical chord symbols that is simple and intuitive for musically trained individuals to write and understand, yet highly structured and unambiguous to parse with computer programs. When designing feature extraction algorithms, it is important to have a hand annotated test set providing a ground truth to(More)
We investigate a data-driven approach to the analysis and transcription of polyphonic music, using a probabilistic model which is able to find sparse linear decompositions of a sequence of short-term Fourier spectra. The resulting system represents each input spectrum as a weighted sum of a small number of "atomic" spectra chosen from a larger dictionary;(More)
We introduce a new model for extracting end points of music structure segments, such as intro, verse, chorus, break and so forth, from recorded music. Our methods are applied to the problem of grouping audio features into continuous structural segments with start and end times corresponding as closely as possible to a ground truth of independent human(More)
We consider two approaches for sparse decomposition of polyphonic music: a timedomain approach based on shift-invariant waveforms, and a frequency-domain approach based on phase-invariant power spectra. When trained on an example of a MIDI-controlled acoustic piano recording, both methods produce dictionary vectors or sets of vectors which represent(More)
We introduce an information theoretic measure of statistical structure, called ‘binding information’, for sets of random variables, and compare it with several previously proposed measures including excess entropy, Bialek et al.’s predictive information, and the multi-information. We derive some of the properties of the binding information, particularly in(More)
2 In this article, we give an overview of a range of approaches to the analysis and separation of musical audio. In particular, we consider the problems of automatic music transcription and audio source separation, which are of particular interest to our group. Monophonic music transcription, where a single note is present at one time, can be tackled using(More)
Previous work has shown that various flavours of Independent Component Analysis, when applied to natural images, all result in broadly similar localised, oriented band-pass feature detectors, which have been likened to wavelets or edge detectors. In this paper, we present a similar analysis of ‘natural’ sounds drawn from two radio stations: one broadcasting(More)
Most sound scenes result from the superposition of several sources, which can be separately perceived and analyzed by human listeners. Source separation aims to provide machine listeners with similar skills by extracting the sounds of individual sources from a given scene. Existing separation systems operate either by emulating the human auditory system or(More)