Juan Pablo Bello

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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)
When considering the problem of audio-to-audio matching, determining musical similarity using low-level features such as Fourier transforms and MFCCs is an extremely difficult task, as there is little semantic information available. Full semantic transcription of audio is an unreliable and imperfect task in the best case, an unsolved problem in the worst.(More)
Automatic urban sound classification is a growing area of research with applications in multimedia retrieval and urban informatics. In this paper we identify two main barriers to research in this area - the lack of a common taxonomy and the scarceness of large, real-world, annotated data. To address these issues we present a taxonomy of urban sounds and a(More)
We present a study on the combined use of energy and phase information for the detection of onsets in musical signals. The resulting method improves upon both energy-based and phase-based approaches. The detection function, generated from the analysis of the signal in the complex frequency domain is sharp at the position of onsets and smooth everywhere(More)
We describe an unsupervised, data-driven, method for automatically identifying repeated patterns in music by analyzing a feature matrix using a variant of sparse convolutive non-negative matrix factorization. We utilize sparsity constraints to automatically identify the number of patterns and their lengths, parameters that would normally need to be fixed in(More)
Sonic Visualiser is the name for an implementation of a system to assist study and comprehension of the contents of audio data, particularly of musical recordings. It is a C++ application with a Qt4 GUI that runs on Windows, Mac, and Linux. It embodies a number of concepts which are intended to improve interaction with audio data and features, most notably(More)
This paper presents a variation on the theme of using string alignment for MIR in the context of cover song identification in audio collections. Here, the strings are derived from audio by means of HMM-based chord estimation. The characteristics of the cover-song ID problem and the nature of common chord estimation errors are carefully considered. As a(More)
We present a novel method for onset detection in musical signals. It improves over previous energy-based and phase-based approaches by combining both types of information in the complex domain. It generates a detection function that is sharp at the position of onsets and smooth everywhere else. Results on a handlabelled data-set show that high detection(More)
This paper presents a novel method for measuring the structural similarity between music recordings. It uses recurrence plot analysis to characterize patterns of repetition in the feature sequence, and the normalized compression distance, a practical approximation of the joint Kolmogorov complexity, to measure the pairwise similarity between the plots. By(More)