New framework for score segmentation and analysis in OpenMusic

We present new tools for the segmentation and analysis of musical scores in the OpenMusic computer-aided composition environment. A modular object-oriented framework enables the creation of segmentations on score objects and the implementation of automatic or semi-automatic analysis processes. The analyses can be performed and displayed thanks to customizable classes and callbacks. Concrete examples are given, in particular with the implementation of a semi-automatic harmonic analysis system and a framework for rhythmic transcription.

A multimodal genre recognition prototype

In this paper, a multimodal and interactive prototype to perform music genre classification is presented. The system is oriented to multi-part files in symbolic format but it can be adapted using a transcription system to transform audio content in music scores. This prototype uses different sources of information to give a possible answer to the user. It has been developed to allow a human expert to interact with the system to improve its results. In its current implementation, it offers a limited range of interaction and multimodality. Further development aimed at full interactivity and multimodal interactions is discussed.

Recognition of online handwritten music symbols

Paper submitted to MML 2013, 6th International Workshop on Machine Learning and Music, Prague, September 23, 2013.

Improving classification using a Confidence Matrix based on weak classifiers applied to OCR

This paper proposes a new feature representation method based on the construction of a Confidence Matrix (CM). This representation consists of posterior probability values provided by several weak classifiers, each one trained and used in different sets of features from the original sample. The CM allows the final classifier to abstract itself from discovering underlying groups of features. In this work the CM is applied to isolated character image recognition, for which several set of features can be extracted from each sample. Experimentation has shown that the use of CM permits a significant improvement in accuracy in most cases, while the others remain the same. The results were obtained after experimenting with four well-known corpora, using evolved meta-classifiers with the k-Nearest Neighbor rule as a weak classifier and by applying statistical significance tests.

Improving kNN multi-label classification in Prototype Selection scenarios using class proposals

Prototype Selection (PS) algorithms allow a faster Nearest Neighbor classification by keeping only the most profitable prototypes of the training set. In turn, these schemes typically lower the performance accuracy. In this work a new strategy for multi-label classifications tasks is proposed to solve this accuracy drop without the need of using all the training set. For that, given a new instance, the PS algorithm is used as a fast recommender system which retrieves the most likely classes. Then, the actual classification is performed only considering the prototypes from the initial training set belonging to the suggested classes. Results show that this strategy provides a large set of trade-off solutions which fills the gap between PS-based classification efficiency and conventional kNN accuracy. Furthermore, this scheme is not only able to, at best, reach the performance of conventional kNN with barely a third of distances computed, but it does also outperform the latter in noisy scenarios, proving to be a much more robust approach.

Estudio de fiabilidad y viabilidad de la Web 2.0 y la Web semántica para enriquecer lexicones en el dominio farmacológico

Los actuales sistemas de Reconocimiento de Entidades en el dominio farmacológico, necesarios como apoyo para el personal sanitario en el proceso de prescripción de un tratamiento farmacológico, sufren limitaciones relacionadas con la falta de cobertura de las bases de datos oficiales. Parece por tanto necesario analizar la fiabilidad de los recursos actuales existentes, tanto en la Web Semántica como en la Web 2.0, y determinar si es o no viable utilizar dichos recursos como fuentes de información complementarias que permitan generar y/o enriquecer lexicones empleados por sistemas de Reconocimiento de Entidades. Por ello, en este trabajo se analizan las principales fuentes de información relativas al dominio farmacológico disponibles en Internet. Este análisis permite concluir que existe información fiable y que dicha información permitiría enriquecer los lexicones existentes con sinónimos y otras variaciones léxicas o incluso con información histórica no recogida ni mantenida en las bases de datos oficiales.

On the suitability of Prototype Selection methods for kNN classification with distributed data

In the current Information Age, data production and processing demands are ever increasing. This has motivated the appearance of large-scale distributed information. This phenomenon also applies to Pattern Recognition so that classic and common algorithms, such as the k-Nearest Neighbour, are unable to be used. To improve the efficiency of this classifier, Prototype Selection (PS) strategies can be used. Nevertheless, current PS algorithms were not designed to deal with distributed data, and their performance is therefore unknown under these conditions. This work is devoted to carrying out an experimental study on a simulated framework in which PS strategies can be compared under classical conditions as well as those expected in distributed scenarios. Our results report a general behaviour that is degraded as conditions approach to more realistic scenarios. However, our experiments also show that some methods are able to achieve a fairly similar performance to that of the non-distributed scenario. Thus, although there is a clear need for developing specific PS methodologies and algorithms for tackling these situations, those that reported a higher robustness against such conditions may be good candidates from which to start.

Avoiding staff removal stage in optical music recognition: application to scores written in white mensural notation

Staff detection and removal is one of the most important issues in optical music recognition (OMR) tasks since common approaches for symbol detection and classification are based on this process. Due to its complexity, staff detection and removal is often inaccurate, leading to a great number of errors in posterior stages. For this reason, a new approach that avoids this stage is proposed in this paper, which is expected to overcome these drawbacks. Our approach is put into practice in a case of study focused on scores written in white mensural notation. Symbol detection is performed by using the vertical projection of the staves. The cross-correlation operator for template matching is used at the classification stage. The goodness of our proposal is shown in an experiment in which our proposal attains an extraction rate of 96 % and a classification rate of 92 %, on average. The results found have reinforced the idea of pursuing a new research line in OMR systems without the need of the removal of staff lines.

Sistemas y Tecnologías de Información. Tema 1: Introducción

STI: Tema 1. Introducción. La empresa.

Práctica 2. Análisis comparativo de los sistemas educativos japonés y español

El currículo del segundo ciclo de Educación Infantil en la Comunidad Valenciana queda regulado en el Decreto 38/2008. En él se recogen las distintas dimensiones y contenidos a trabajar, y el sistema de evaluación más propicio para esta etapa evolutiva. Este currículo se basa en los principios madurativos, así como los aspectos que como sociedad valoramos fundamentales para el desarrollo integral del niño. Sin embargo, estos valores sociales no siempre coinciden entre culturas o países, lo que puede hacer variar sensiblemente el currículo final. En esta práctica se analizarán las similitudes y diferencias existentes entre los valores y procedimientos de nuestro sistema educativo y el sistema educativo japonés. A través de este análisis el alumno podrá reflexionar y poner en cuestión diferentes aspectos de los sistemas educativos y valorar críticamente los puntos fuertes y débiles de cada uno de ellos.

Sistemas de Control Automático. Práctica 1 (curso 2010-2011)

Práctica 1 de la asignatura sistemas de control automático. Ajuste y sintonización de controladores.

Sistemas de Control Automático. Práctica 2 (curso 2010-2011)

Práctica 2 de sistemas de control automático. Control de velocidad mediante el autómata CP1L y el variador MX2 de Omron.

Sistemas de Control Automático. Práctica 3 (curso 2010-2011)

Práctica 3 de sistemas de control automático. Control de un PLC mediante tramas Host-Link generadas por un PC.

Sistemas de Control Automático. Tema 1: Introducción (curso 2010-2011)

Presentación tema 1 de sistemas de control automático. Introducción.