Jordi Pons

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Many researchers use convolutional neural networks with small rectangular filters for music (spectrograms) classification. First, we discuss why there is no reason to use this filters setup by default and second, we point that more efficient architectures could be implemented if the characteristics of the music features are considered during the design(More)
A common criticism of deep learning relates to the difficulty in understanding the underlying relationships that the neural networks are learning, thus behaving like a blackbox. In this article we explore various architectural choices of relevance for music signals classification tasks in order to start understanding what the chosen networks are learning.(More)
This paper presents an investigation into the detection and classification of drum sounds in polyphonic music and drum loops using non-negative matrix deconvolution (NMD) and the Itakura Saito divergence. The Itakura Saito divergence has recently been proposed as especially appropriate for decomposing audio spectra due to the fact that it is scale(More)
The focus of this work is to study how to efficiently tailor Convolutional Neural Networks (CNNs) towards learning timbre representations from log-mel magnitude spectrograms. We first review the trends when designing CNN architectures. Through this literature overview we discuss which are the crucial points to consider for efficiently learning timbre(More)
En este artículo proponemos un procedimiento objetivo para la evaluación, basada en competencias, de los trabajos fin de grado (TFG) y de máster (TFM) en el contexto de las ingenierías. Dicho procedimiento se ha dividido en seis etapas: (1) definición de las competencias asociadas al TFG o al TFM y de indicadores objetivos; (2) definición de los momentos(More)
Music perception remains rather poor for many Cochlear Implant (CI) users due to the users' deficient pitch perception. However, comprehensible vocals and simple music structures are well perceived by many CI users. In previous studies researchers re-mixed songs to make music more enjoyable for them, favoring the preferred music elements (vocals or beat)(More)
We approach the singing phrase audio to score matching problem by using phonetic and duration information – with a focus on studying the jingju a cappella singing case. We argue that, due to the existence of a basic melodic contour for each mode in jingju music, only using melodic information (such as pitch contour) will result in an ambiguous matching.(More)
This paper introduces a new score-informed method for the segmentation of jingju a cappella singing phrase into syllables. The proposed method estimates the most likely sequence of syllable boundaries given the estimated syllable onset detection function (ODF) and its score. Throughout the paper, we first examine the jingju syllables structure and propose a(More)
  • DOCUMENTS DE TREBALL, DE LA DIVISIÓ, Daniel A. Tirado, Jordi Pons, Daniel A. Tirado Fabregat, Jordi Pons Novell
  • 2003
This study presents new evidence concerning the uneven processes of industrialization in nineteenth century Spain and Italy based on a disaggregate analysis of the productive sectors from which the behaviour of the aggregate indices is comprised. The use of multivariate time-series analysis techniques can aid our understanding and characterization of these(More)