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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 describe a method of segmenting musical audio into structural sections based on a hierarchical labeling of spectral features. Frames of audio are first labeled as belonging to one of a number of discrete states using a hidden Markov model trained on the features. Histograms of neighboring frames are then clustered into segment-types representing distinct(More)
We present a content-based automatic music tagging algorithm using fully convolutional neural networks (FCNs). We evaluate different architectures consisting of 2D con-volutional layers and subsampling layers only. In the experiments , we measure the AUC-ROC scores of the archi-tectures with different complexities and input types using the MagnaTagATune(More)
In this paper, we describe current efforts towards interlink-ing music-related datasets on the Web. We first explain some initial interlinking experiences, and the poor results obtained by taking a na¨ıve approach. We then detail a particular interlinking algorithm, taking into account both the similarities of web resources and of their neighbours. We(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)
The promise of the Semantic Web is to democratise access to data, allowing anyone to make use of and contribute back to the global store of knowledge. Within the scope of the OMRAS2 Music Information Retrieval project, we have made use of and contributed to Semantic Web technologies for purposes ranging from the publication of music recording metadata to(More)