Andrés Eduardo Coca Salazar - Profile on Academia.edu (original) (raw)

Videos by Andrés Eduardo Coca Salazar

Symphonic work inspired by Palestinian-Israeli conflict. YouTube: is.gd/WHL_YT

4 views

Papers by Andrés Eduardo Coca Salazar

Research paper thumbnail of Music genre classification using centrality measures of complex brain connectivity networks

Anais do Encontro Nacional de Inteligência Artificial e Computacional (ENIAC), 2024

Estímulos externos podem alterar a atividade cerebral, trazendo consigo mudanças comportamentais ... more Estímulos externos podem alterar a atividade cerebral, trazendo consigo mudanças comportamentais e/ou emocionais. O estudo desses efeitos serve para extrair informação que pode ser aplicada em sistemas de classificação personalizada. Neste artigo, é proposta uma metodologia para classificar o eletroencefalograma (EEG) segundo o gênero de um estímulo musical, usando a informação estrutural da conectividade funcional (FC) entre eletrodos e a sua representação e mineração com redes complexas. Para tal, após ter o sinal pré-processado, foi determinada a FC mediante correlação (Co) e PLV (Phase-Locking Value). Para a rede de eletrodos resultante, foram calculadas medidas topológicas globais de integração, resiliência e segregação. Além disso, para complementar a matriz de características, também foram calculadas medidas intra-elétrodos, porém somente para os nós com maior centralidade. Dado que as redes são ponderadas, aqui são propostas seis novas medidas de centralidade (C(p)ks) usando o grau e a força local, previamente normalizadas e balanceadas com um fator de sintonia (α), e combinadas considerando: 1) força média do nó, 2) ponto médio (aritmético, harmônico, geométrico e quadrático), ou 3) potencializando a interação mútua. Posteriormente, foram calculadas medidas convencionais de séries de tempo para os primeiros nk canais mais centrais, obtendo um vetor de características de dimensão variável. No aprendizado de máquina, foi usado um classificador de ensemble com 10-validação cruzada repetida 10 vezes. Experimentos com Co e PLV; para cada C(p)ks, e variando nk e α; revelaram que é possível identificar, com uma acurácia de 57.4%, o gênero musical analisando apenas os canais mais sincronizados e com maior intensidade.

Research paper thumbnail of CLBP Texture Descriptor in Multipartite Complex Network Configuration for Music Genre Classification

International Neural Network Society Workshop on Deep Learning Innovations and Applications (INNS DLIA) - International Joint Conference on Neural Networks (IJCNN) , 2023

Music genres define the characteristics that musical pieces must have to belong to a given class.... more Music genres define the characteristics that musical pieces must have to belong to a given class. These characteristics are reflected in the audio signal and, consequently, in the image that represents its spectral content: the spectrogram. In this paper, we propose a Music Genre Classification (MGC) system based on representation with complex networks of CLBP (Completed Local Binary Pattern) texture descriptor codes extracted from spectrograms: mel-spectrogram and gammatonegram. Complex networks were generated using CLBP codes in multipartite configuration: mono, bi, and tripartite networks; where the three node types are signal (CLBP-S), magnitude (CLBP-M) and central (CLBP-C) codes. The networks were mined using conventional, textural, and bi and tripartite topological measures. In order to test the proposed MGC, we used the GTZAN dataset and defined several experiments using combinations of multipartite measures: 1) monopartite, 2) mono and bipartite, and 3) mono, bi and tripartite. All experiments were performed for each spectrogram individually and jointly. In the machine learning stage, we used the ensemble classifier Bagging with Random Forest, and 10-fold cross-validation repeated 100 times. As a main result, it was found that the bipartite measures related to CLBP-C decrease the performance, but the tripartites increased it. Moreover, in most experiments using only gammatonogram the performance was better. Consequently, the experiment using tripartite measures extracted from the gammatonegram revealed a satisfactory result, indicating that the proposed MGC is promising.

Research paper thumbnail of GLSI Texture Descriptor Based on Complex Networks for Music Genre Classification

International Joint Conference on Neural Networks (IJCNN) , 2023

The texture classification of an image is related to an important musical attribute, the music ge... more The texture classification of an image is related to an important musical attribute, the music genre. This relationship is depicted in the visual representation of the audio signal, called as spectrogram. In this paper, we propose a new Music Genre Classification (MGC) system that processes the spectrogram texture using the Gray Level and Structural Information (GLSI) descriptor, and represents the interconnection between the descriptor codes through complex networks. The GLSI descriptor is an improvement of the CLBP (Completed Local Binary Pattern) descriptor, which quantifies the texture of an image with three codes: signal (CLBP-S), magnitude (CLBP-M), and central (CLBP-C). By transforming the CLBP-C code, GLSI adds macro-structural information. The network nodes represent the descriptor codes, and the respective edges, the relationship according to the horizontal and vertical consecutive condition. We defined two representations for the nodes: 1) individual code node, obtaining the Gs, Gm and Gg networks, and 2) triple code node, obtaining the Gsmg network. For the experimental stage, we used the GTZAN dataset, three types of spectrograms: conventional, mel-spectrogram and gammatonegram; and mining with network topological measures. For each type of spectrogram, we performed three experiments according to feature vector combinations, such as measures of: 1) Gs, Gm and Gg, 2) Gsmg, and 3) all networks. In the machine learning stage, we used the ensemble classifier Bagging with Random Forest, and 10fold cross-validation repeated 100 times. The experiment using all measures and all spectrograms revealed a satisfactory result, indicating that the MGC proposed is promising. We also propose a new equation to calculate the GLSI code, which proved to be much faster and with more intuitive encoding.

Research paper thumbnail of Neural Networks And Ensemble Based Architectures To Automatic Musical Harmonization: A Performance Comparison

Applied Artificial Intelligence, 2023

Harmony can be defined in a musical way as art that combines several musical notes reproduced sim... more Harmony can be defined in a musical way as art that combines several musical notes reproduced simultaneously to create sounds that are coherent to human ears and serve as accompaniment and filling. However, working out harmony is not a simple task. It requires knowledge, experience, and an intense study of music theory, which takes time to reach good skills. Thus, systems capable of automatically harmonizing melodies are beneficial for experienced and novice musicians. In this paper, a comparative study between distinct architectures and ensembles of Artificial Neural Networks was proposed to solve the problem of musical harmonization, seeking consistent results with rules of music theory: Multilayer Perceptron (MLP), Radial Basis Function network (RBF), Echo State Network (ESN), Extreme Learning Machines (ELM), and Long Short-Term Memory (LSTM). For this, a processed and defined melody with symbolic musical data serves as input to the system, having been trained from a musical database that contains melody and harmony. The output is the chord sequence to be applied to the melody. The results were analyzed with quantitative measures and the ability to melody adaptation. The performances were favorable to the MLP, which could generate harmonies according to the objectives.

Research paper thumbnail of Hierarchical mining with complex networks for music genre classification

Digital Signal Processing, Apr 8, 2022

Music genre is an important feature to identify a musical work. Thus, it is the most used label t... more Music genre is an important feature to identify a musical work. Thus, it is the most used label to organize musical datasets. However, this label is not always available and its identification is not a simple and direct task. Hence, in literature we can find many music genre classification (MGC) methods, with a variety of features and machine learning algorithms (MLA). In this paper, we propose an MGC system by using two levels of hierarchical mining, GLCM (gray level co-occurrence matrix) networks generated from the mel-spectrogram and a multi-hybrid feature strategy. Three types of complex networks were generated: GLCM network Gg, Superpixels network Gs, and GLCM network of each node of Gs (Ggsi network). The multi-hybrid features are formed by textural and topological measures of complex networks and acoustic measures. In the classification step, we used three datasets: GTZAN, Homburg, and ISMIR; two MLAs belonging to the classifier ensemble approach, and (10)-fold cross-validation repeated 100 times. Several experiments were performed using feature combinations of macro-mining (global features of Gg and Gs) and micro-mining (global features of Ggsi). For GTZAN, we performed a detailed analysis of individual class performance and calculated our new ranking logarithmic score (RLS) applied to the F1-score. For all datasets, the RLS and accuracy values were compared with several state-of-the-art methods. The accuracy obtained using micro-mining was >90%, which reveals a satisfactory result.

Research paper thumbnail of Optical Digital Theremin with Audio Synthesis and Graphic Interface

INTERNATIONAL JOURNAL OF CIRCUITS, SYSTEMS AND SIGNAL PROCESSING, 2021

The theremin is one of the first electronic musical instruments and one of the few played without... more The theremin is one of the first electronic musical instruments and one of the few played without physical contact since it only requires hand and finger movements to control the amplitude and frequency of the musical note. However, the capacitive functioning of the antennas increases the sensitivity to electrical interference, its timbre is fixed, and the frequency antenna's vertical arrangement could limit the use of people with amputated fingers. Furthermore, it does not contain any help to guide the execution, which makes it a very difficult instrument to play. In this paper, we present the development of a digital optical theremin with an audio synthesis process, intuitive graphical interface, frequency antenna in the horizontal position, and linearization of the frequency-distance relationship. These features are intended to aid learning and interpretation of the instrument and extend access to people with finger limitations. In order to validate the instrument's behavior and characteristics, we conducted three experiments: 1) accuracy analysis of the linearization through the mean absolute error in units of cents and the Kruskal-Wallis statistical inference test, 2) validation of the steps of the audio synthesis module, and 3) checking of the timbral diversity, both through the Fourier spectrum. This prototype could be used as an auxiliary tool in musical initiation and the development of musical perception.

Research paper thumbnail of Musical rhythmic pattern extraction using relevance of communities in networks

Information Sciences, 2016

The rhythmic background of a musical piece is usually composed of featured elements that define t... more The rhythmic background of a musical piece is usually composed of featured elements that define the musical genre. For each song, such elements form rhythmic patterns, the most repetitive ones defines the rhythm of a specific musical genre and the less frequent ones correspond to fortuitous patterns that comply a transition, diversification, introduction or conclusion function. In this paper, we introduce a network-based method for automatic extraction of rhythmic pattern of a single song. We also propose a method for rhythmic summarization of a set of songs from the same genre, artist, and combinations of genres and artists. The method can be used to extract any type of rhythm pattern, both monophonic and polyphonic, represented by symbolic data. A musical piece is generally formed by one or more predefined rhythmic patterns and such patterns are composed of rhythmic cells (RCs), which are groups of rhythmic figures derived from nth division of a larger rhythmic figure. At the pre-processing and encoding phases of the proposed method, the RCs of drums percussion lines are represented in duration-weighted notation (DWN). Then, the vector of DWN is encoded to be free of the dimensional dependence on the number of figures in the RC. After that, a network is constructed from the encoded DWN using the method proposed in this paper. We find that the rhythmic patterns of the musical work are related to the formation of communities in the constructed music network. In order to confirm such a finding, three network community detection algorithms are applied: Modularity Optimization algorithm and Louvain algorithm for the disjoint community detection, and Bayesian Non-negative Matrix Factorization algorithm for detecting overlapped communities. Furthermore, a new measure for quantifying the relevance of communities to differentiate types of rhythmic patterns is introduced. The proposed technique has been applied to automatic extraction of rhythmic pattern and rhythmic summarization of the songs of The Beatles, Bob Marley, and other artists, respectively. The results show that the method of extraction and summarization has good performance.

Research paper thumbnail of Dodecaphonic Composer Identification Based On Complex Networks

BRACIS, 2019

In the musical composition process, even subconsciously, it is common for composers to imprint th... more In the musical composition process, even subconsciously, it is common for composers to imprint their personal signature implicitly within the work. This characteristic allows the recognition and the individualization of its origin through the sound assembly. With this in mind, the composer identification through the signature in his works allow us to classify a musical genre into more specific subcategories. However, the characteristics of that signature are of such great variation that make identification task difficult. This paper proposes the use of data mining within complex networks and machine learning techniques to classify a dodecaphonic musical work according to its composer. Considering the dodecaphonic matrix, two types of networks were generated: 1) intervals and 2) series. The feature vector is composed of new melodic topological measures adapted to the calculation from the adjacency matrix and conventional topological measurements. The classifiers Random Forest, AdaBoost and Random Subspace returned high values of accuracy and AUC (> 90%) in the identification of composers Schoenberg, Stravinsky and Webern. Confirming the existence of a relation among the characteristics of the original series, the selection and application of derived series and the composer. The results obtained revealed a good performance and showed that the experiment is very promising.

Research paper thumbnail of Characterization and identification of twelve-tone composers

ENIAC, 2018

The individualism of each composer is shaped in an inherent way to his personality, aiming for re... more The individualism of each composer is shaped in an inherent way to his personality, aiming for recognition of particular form through the own songs. In this way, it is possible to categorize a musical subgenre at a deeper level by identifying the composer from his works. However, the characteristics of each composer are so varied that they are difficult to identify. In this paper it is proposed to use machine learning to classify works of twelve-tone music according to the composer, under the hypothesis that in choosing the twelve-tone series a part of his signature was reflected. Experimental results showed promising performance and confirmed the existence of a relation between composer and series. Resumo. O individualismo de cada compositorécompositor´compositoré plasmado de forma inerente a sua personalidade, visando o seu reconhecimento particular através das suas próprias músicas. Desta forma, ´ e possível categorizar um subgênero musical em um nível mais profundo mediante a identificaçidentificaç˜identificação do compositor a partir das suas obras. No entanto, as características de cada compositor são tão variadas que dificultam sua identificaçidentificaç˜identificação. Neste artigó e proposto usar aprendizado de máquina para classificar obras de música dodecafônica segundo o compositor, sob a hipótese de que na escolha da série dodecafônica ficou refletida uma parte da sua assinatura. Resultados experimentais mostraram desempenho promissor e confirmaram a evidencia da existência de uma relaçrelaç˜relação entre compositor-série. 1. IntroduçIntroduç˜Introdução O crescimento constante dos bancos de dados musicais disponíveis digitalmente tem mo-tivado o desenvolvimento de diferentes métodos de classificaçclassificaç˜classificação automática de música. Tipicamente, tais métodos têm sido direcionados maioritariamente para a classificaçclassificaç˜classificação de gêneros musicais, a qual tem sido abordada desde diferentes perspectivas [1, 14, 17]. Contudo, outros níveis de classificaçclassificaç˜classificação são possíveis, como classificaçclassificaç˜classificação em subgêneros [15] e em estilos [16]. No entanto, após ter classificado determinado banco de dados em algum dos dois anteriores níveis, tambémtambém´tambémétambémé´tambéméútil discriminar cada categoria obtida em uma subcategoria mais profunda, o compositor, deixando-o assim mais organizado e preparado para ser utilizado em outros sistemas, como sistema de recomendaçrecomendaç˜recomendação [13] ou sistemas de análise e extraçextraç˜extração de dados [18], dentre outros. O fundamento principal por trás da tarefa de identificaçidentificaç˜identificação do compositorécompositor´compositoré que um alvo procurado por quase todos os compositores musicaisémusicais´musicaisé impregnar nas suas obras a sua assinatura musical para assim poderem ser reconhecidos através delas. Em muitos casos esse processó e inconsciente, e nasce da essência intrínseca do compositor na sua

Research paper thumbnail of Computer-Aided Music Composition with LSTM Neural Network and Chaotic Inspiration

IJCNN, 2013

In this paper a new neural network system for composition of melodies is proposed. The Long Short... more In this paper a new neural network system for composition of melodies is proposed. The Long Short-Term Memory (LSTM) neural network is adopted as the neural network model. We include an independent melody as an additional input in order to provide an inspiration source to the network. This melody is given by a chaotic composition algorithm and works as an inspiration to the network enhancing the subjective measure of the composed melodies. As the chaotic system we use the Hénon map with two variables, which are mapped to pitch and rhythm. We adopt a measure to conduct the degree of melodiousness (Euler's gradus suavitatis) of the output melody, which is compared with a reference value. Varying a specific parameter of the chaotic system, we can control the complexity of the chaotic melody. The system runs until the degree of melodiousness falls within a predetermined range.

Research paper thumbnail of Musical Scales Recognition via Deterministic Walk in a Graph

BRACIS, 2016

Musical scales play an important role in melodies, since its properties are reflected to the melo... more Musical scales play an important role in melodies, since its properties are reflected to the melodic essence. The extraction and understanding of scales are essential in both analysis and composition of music. However, the scale identification is a nontrivial task. Consequently, classic algorithms for identifying scales have been developed based on the most popular scales, such as major and minor scales. In this paper, we propose a comprehensive method for identifying musical scales, which allows to detect a wide range of scales beyond the traditional ones. Our method uses a deterministic walk through the nodes of a graph, where each node represents a valid interval structure. The transition between nodes is performed following a validation rule that governs the fragmentation of intervals. Moreover, if the scale is incomplete, possible structures can be determined and the scale is estimated according to the harmonic similarity percentage measure. The proposed method has been tested using a database of Finnish folk melodies and a data set of random melodies composed using rarely used scales. Experimental results show good performance of the proposed technique.

Research paper thumbnail of Identification of Music Genres by Using Communities Detection in Complex Networks

ENIAC , 2015

In this paper, we propose a new methodology for identification of musical genres in symbolic data.

Research paper thumbnail of Rhythmic Pattern Extraction by Community Detection in Complex Networks

BRACIS, 2014

In this paper, we study musical knowledge extraction and discrimination. Specifically, we propose... more In this paper, we study musical knowledge extraction and discrimination. Specifically, we propose a method for automatic extraction of drums rhythmic patterns of music and the rhythmic summarization of a set of songs from the same artist. A musical piece is generally formed of one or more predefined rhythmic patterns and such patterns are composed of Rhythmic Cells (RC), which are groups of rhythmic figures derived from n-th division of a larger rhythmic figure. At the pre-processing and encoding phase, the RCs of drums percussion lines are represented in Duration-Weighted Notation (DWN). Then, the vector of DWM is encoded to be free of the dimensional dependence on the number of figures in the RC. After that, a network is constructed from the encoded DWM using the method proposed in this paper. We find that the rhythmic patterns of the musical work are related to the formation of communities in the network. In this work, two community detection algorithms are used: Louvain algorithm for the disjoint community detection and Bayesian Nonnegative Matrix Factorization (BNMF) algorithm for detecting overlapping communities. Moreover, a new measure for quantifying the relevance of communities to differentiate types of rhythmic patterns is introduced. The proposed technique has been applied to automatic extraction of drums rhythmic pattern of the song "Drive my car'' by The Beatles. Experimental results show good performance of the proposed method.

Research paper thumbnail of Characterizing chaotic melodies in automatic music composition

Chaos: An Interdisciplinary Journal of Nonlinear Science, 2010

In this paper, we initially present an algorithm for automatic composition of melodies using chao... more In this paper, we initially present an algorithm for automatic composition of melodies using chaotic dynamical systems. Afterward, we characterize chaotic music in a comprehensive way as comprising three perspectives: musical discrimination, dynamical influence on musical features, and musical perception. With respect to the first perspective, the coherence between generated chaotic melodies (continuous as well as discrete chaotic melodies) and a set of classical reference melodies is characterized by statistical descriptors and melodic measures. The significant differences among the three types of melodies are determined by discriminant analysis. Regarding the second perspective, the influence of dynamical features of chaotic attractors, e.g., Lyapunov exponent, Hurst coefficient, and correlation dimension, on melodic features is determined by canonical correlation analysis. The last perspective is related to perception of originality, complexity, and degree of melodiousness (Euler’s gradus suavitatis) of chaotic and classical melodies by nonparametric statistical tests.

© 2010 American Institute of Physics

Research paper thumbnail of Generation of composed musical structures through recurrent neural networks based on chaotic inspiration

IJCNN, 2011

In this work, an Elman recurrent neural network is used for automatic musical structure compositi... more In this work, an Elman recurrent neural network
is used for automatic musical structure composition based on
the style of a music previously learned during the training
phase. Furthermore, a small fragment of a chaotic melody is
added to the input layer of the neural network as an inspiration
source to attain a greater variability of melodies. The neural
network is trained by using the BPTT (back propagation through
time) algorithm. Some melody measures are also presented for
characterizing the melodies provided by the neural network and
for analyzing the effect obtained by the insertion of chaotic
inspiration in relation to the original melody characteristics.
Specifically, a similarity melodic measure is considered for
contrasting the variability obtained between the learned melody
and each one of the composite melodies by using different
quantities of inspiration musical notes.

Research paper thumbnail of Chaotic Melody Generation and Statistical Characterization - Andrés Coca, Zhao Liang and Gerard Olivar

Dynamics Days South America , 2010

keywords: Applications of Nonlinear Sciences Chaotic Dynamics.

Research paper thumbnail of Controlando melodías caóticas - A. Coca, G. Olivar y Z. Liang

Se presenta el desarrollo de un algoritmo para la composición automática de melodías a partir de ... more Se presenta el desarrollo de un algoritmo para la composición automática de melodías a partir de sistemas dinámicos no lineales (caóticos o no caóticos). Las variables de solución de los sistemas son usadas para la extracción de las variables musicales que constituyen la melodía (altura, ritmo y velocidad). Las variables musicales pueden ser acondicionadas según algunas especificaciones musicales de entrada. Se destaca la posibilidad de crear melodías con escalas microtonales y la facultad de disponer del conjunto total de escalas y modos posibles en el sistema temperado. Las técnicas para el control del caos OGY, TDAS y FPIC son utilizadas independientemente para controlar directamente el sistema caótico e indirectamente la melodía generada. Dependiendo de la estrategia de control empleada, el atractor puede evolucionar a una órbita periódica o a un punto fijo de periodo n. El reflejo musical de esto es la transformación de la melodía en una frase musical repetitiva, un grupo consecutivo de notas (arpegio) o una nota musical sostenida.

Research paper thumbnail of Controlling Chaotic Melodies - A. Coca, G. Olivar and Z. Liang

ENIP, 2009, 2009

This paper presents an algorithm for automatic composition of melodies by using nonlinear dynamic... more This paper presents an algorithm for automatic composition of
melodies by using nonlinear dynamical systems. The variables
of the systems are used for extraction of components that
constitute the musical melody (pitch, rhythm and dynamics)
which can be adjusted according to specific musical input. It
should be highlighted that the proposed algorithm not only can
generate melodies with microtonal scales, but also is capable
of having the whole set of possible scales and modes in the
temperated system. Techniques for control of chaos are used to
transform the chaotic attractor to a periodic or a fixed point
attractor, generating melody of a repeated musical phrase, a
series of consecutive notes (arpeggio) or a sustained musical
note.

Research paper thumbnail of Desarrollo y aplicación de un algoritmo para la distribución de melodías en varias voces 2

Andrés Eduardo Coca S. * Resumen -Se presenta el desarrollo, la implementación y la aplicación de... more Andrés Eduardo Coca S. * Resumen -Se presenta el desarrollo, la implementación y la aplicación de un algoritmo para distribuir las notas de una o varias melodías de forma organizada y sistemática. Se muestran los resultados obtenidos al distribuir las notas de la escala cromática, para crear una ilusión acústica. Esta ilusión es utilizada en la composición automatizada de algunos compases de la obra para cuarteto de cuerdas clásico Pitch Music.

Symphonic work inspired by Palestinian-Israeli conflict. YouTube: is.gd/WHL_YT

4 views

Research paper thumbnail of Music genre classification using centrality measures of complex brain connectivity networks

Anais do Encontro Nacional de Inteligência Artificial e Computacional (ENIAC), 2024

Estímulos externos podem alterar a atividade cerebral, trazendo consigo mudanças comportamentais ... more Estímulos externos podem alterar a atividade cerebral, trazendo consigo mudanças comportamentais e/ou emocionais. O estudo desses efeitos serve para extrair informação que pode ser aplicada em sistemas de classificação personalizada. Neste artigo, é proposta uma metodologia para classificar o eletroencefalograma (EEG) segundo o gênero de um estímulo musical, usando a informação estrutural da conectividade funcional (FC) entre eletrodos e a sua representação e mineração com redes complexas. Para tal, após ter o sinal pré-processado, foi determinada a FC mediante correlação (Co) e PLV (Phase-Locking Value). Para a rede de eletrodos resultante, foram calculadas medidas topológicas globais de integração, resiliência e segregação. Além disso, para complementar a matriz de características, também foram calculadas medidas intra-elétrodos, porém somente para os nós com maior centralidade. Dado que as redes são ponderadas, aqui são propostas seis novas medidas de centralidade (C(p)ks) usando o grau e a força local, previamente normalizadas e balanceadas com um fator de sintonia (α), e combinadas considerando: 1) força média do nó, 2) ponto médio (aritmético, harmônico, geométrico e quadrático), ou 3) potencializando a interação mútua. Posteriormente, foram calculadas medidas convencionais de séries de tempo para os primeiros nk canais mais centrais, obtendo um vetor de características de dimensão variável. No aprendizado de máquina, foi usado um classificador de ensemble com 10-validação cruzada repetida 10 vezes. Experimentos com Co e PLV; para cada C(p)ks, e variando nk e α; revelaram que é possível identificar, com uma acurácia de 57.4%, o gênero musical analisando apenas os canais mais sincronizados e com maior intensidade.

Research paper thumbnail of CLBP Texture Descriptor in Multipartite Complex Network Configuration for Music Genre Classification

International Neural Network Society Workshop on Deep Learning Innovations and Applications (INNS DLIA) - International Joint Conference on Neural Networks (IJCNN) , 2023

Music genres define the characteristics that musical pieces must have to belong to a given class.... more Music genres define the characteristics that musical pieces must have to belong to a given class. These characteristics are reflected in the audio signal and, consequently, in the image that represents its spectral content: the spectrogram. In this paper, we propose a Music Genre Classification (MGC) system based on representation with complex networks of CLBP (Completed Local Binary Pattern) texture descriptor codes extracted from spectrograms: mel-spectrogram and gammatonegram. Complex networks were generated using CLBP codes in multipartite configuration: mono, bi, and tripartite networks; where the three node types are signal (CLBP-S), magnitude (CLBP-M) and central (CLBP-C) codes. The networks were mined using conventional, textural, and bi and tripartite topological measures. In order to test the proposed MGC, we used the GTZAN dataset and defined several experiments using combinations of multipartite measures: 1) monopartite, 2) mono and bipartite, and 3) mono, bi and tripartite. All experiments were performed for each spectrogram individually and jointly. In the machine learning stage, we used the ensemble classifier Bagging with Random Forest, and 10-fold cross-validation repeated 100 times. As a main result, it was found that the bipartite measures related to CLBP-C decrease the performance, but the tripartites increased it. Moreover, in most experiments using only gammatonogram the performance was better. Consequently, the experiment using tripartite measures extracted from the gammatonegram revealed a satisfactory result, indicating that the proposed MGC is promising.

Research paper thumbnail of GLSI Texture Descriptor Based on Complex Networks for Music Genre Classification

International Joint Conference on Neural Networks (IJCNN) , 2023

The texture classification of an image is related to an important musical attribute, the music ge... more The texture classification of an image is related to an important musical attribute, the music genre. This relationship is depicted in the visual representation of the audio signal, called as spectrogram. In this paper, we propose a new Music Genre Classification (MGC) system that processes the spectrogram texture using the Gray Level and Structural Information (GLSI) descriptor, and represents the interconnection between the descriptor codes through complex networks. The GLSI descriptor is an improvement of the CLBP (Completed Local Binary Pattern) descriptor, which quantifies the texture of an image with three codes: signal (CLBP-S), magnitude (CLBP-M), and central (CLBP-C). By transforming the CLBP-C code, GLSI adds macro-structural information. The network nodes represent the descriptor codes, and the respective edges, the relationship according to the horizontal and vertical consecutive condition. We defined two representations for the nodes: 1) individual code node, obtaining the Gs, Gm and Gg networks, and 2) triple code node, obtaining the Gsmg network. For the experimental stage, we used the GTZAN dataset, three types of spectrograms: conventional, mel-spectrogram and gammatonegram; and mining with network topological measures. For each type of spectrogram, we performed three experiments according to feature vector combinations, such as measures of: 1) Gs, Gm and Gg, 2) Gsmg, and 3) all networks. In the machine learning stage, we used the ensemble classifier Bagging with Random Forest, and 10fold cross-validation repeated 100 times. The experiment using all measures and all spectrograms revealed a satisfactory result, indicating that the MGC proposed is promising. We also propose a new equation to calculate the GLSI code, which proved to be much faster and with more intuitive encoding.

Research paper thumbnail of Neural Networks And Ensemble Based Architectures To Automatic Musical Harmonization: A Performance Comparison

Applied Artificial Intelligence, 2023

Harmony can be defined in a musical way as art that combines several musical notes reproduced sim... more Harmony can be defined in a musical way as art that combines several musical notes reproduced simultaneously to create sounds that are coherent to human ears and serve as accompaniment and filling. However, working out harmony is not a simple task. It requires knowledge, experience, and an intense study of music theory, which takes time to reach good skills. Thus, systems capable of automatically harmonizing melodies are beneficial for experienced and novice musicians. In this paper, a comparative study between distinct architectures and ensembles of Artificial Neural Networks was proposed to solve the problem of musical harmonization, seeking consistent results with rules of music theory: Multilayer Perceptron (MLP), Radial Basis Function network (RBF), Echo State Network (ESN), Extreme Learning Machines (ELM), and Long Short-Term Memory (LSTM). For this, a processed and defined melody with symbolic musical data serves as input to the system, having been trained from a musical database that contains melody and harmony. The output is the chord sequence to be applied to the melody. The results were analyzed with quantitative measures and the ability to melody adaptation. The performances were favorable to the MLP, which could generate harmonies according to the objectives.

Research paper thumbnail of Hierarchical mining with complex networks for music genre classification

Digital Signal Processing, Apr 8, 2022

Music genre is an important feature to identify a musical work. Thus, it is the most used label t... more Music genre is an important feature to identify a musical work. Thus, it is the most used label to organize musical datasets. However, this label is not always available and its identification is not a simple and direct task. Hence, in literature we can find many music genre classification (MGC) methods, with a variety of features and machine learning algorithms (MLA). In this paper, we propose an MGC system by using two levels of hierarchical mining, GLCM (gray level co-occurrence matrix) networks generated from the mel-spectrogram and a multi-hybrid feature strategy. Three types of complex networks were generated: GLCM network Gg, Superpixels network Gs, and GLCM network of each node of Gs (Ggsi network). The multi-hybrid features are formed by textural and topological measures of complex networks and acoustic measures. In the classification step, we used three datasets: GTZAN, Homburg, and ISMIR; two MLAs belonging to the classifier ensemble approach, and (10)-fold cross-validation repeated 100 times. Several experiments were performed using feature combinations of macro-mining (global features of Gg and Gs) and micro-mining (global features of Ggsi). For GTZAN, we performed a detailed analysis of individual class performance and calculated our new ranking logarithmic score (RLS) applied to the F1-score. For all datasets, the RLS and accuracy values were compared with several state-of-the-art methods. The accuracy obtained using micro-mining was >90%, which reveals a satisfactory result.

Research paper thumbnail of Optical Digital Theremin with Audio Synthesis and Graphic Interface

INTERNATIONAL JOURNAL OF CIRCUITS, SYSTEMS AND SIGNAL PROCESSING, 2021

The theremin is one of the first electronic musical instruments and one of the few played without... more The theremin is one of the first electronic musical instruments and one of the few played without physical contact since it only requires hand and finger movements to control the amplitude and frequency of the musical note. However, the capacitive functioning of the antennas increases the sensitivity to electrical interference, its timbre is fixed, and the frequency antenna's vertical arrangement could limit the use of people with amputated fingers. Furthermore, it does not contain any help to guide the execution, which makes it a very difficult instrument to play. In this paper, we present the development of a digital optical theremin with an audio synthesis process, intuitive graphical interface, frequency antenna in the horizontal position, and linearization of the frequency-distance relationship. These features are intended to aid learning and interpretation of the instrument and extend access to people with finger limitations. In order to validate the instrument's behavior and characteristics, we conducted three experiments: 1) accuracy analysis of the linearization through the mean absolute error in units of cents and the Kruskal-Wallis statistical inference test, 2) validation of the steps of the audio synthesis module, and 3) checking of the timbral diversity, both through the Fourier spectrum. This prototype could be used as an auxiliary tool in musical initiation and the development of musical perception.

Research paper thumbnail of Musical rhythmic pattern extraction using relevance of communities in networks

Information Sciences, 2016

The rhythmic background of a musical piece is usually composed of featured elements that define t... more The rhythmic background of a musical piece is usually composed of featured elements that define the musical genre. For each song, such elements form rhythmic patterns, the most repetitive ones defines the rhythm of a specific musical genre and the less frequent ones correspond to fortuitous patterns that comply a transition, diversification, introduction or conclusion function. In this paper, we introduce a network-based method for automatic extraction of rhythmic pattern of a single song. We also propose a method for rhythmic summarization of a set of songs from the same genre, artist, and combinations of genres and artists. The method can be used to extract any type of rhythm pattern, both monophonic and polyphonic, represented by symbolic data. A musical piece is generally formed by one or more predefined rhythmic patterns and such patterns are composed of rhythmic cells (RCs), which are groups of rhythmic figures derived from nth division of a larger rhythmic figure. At the pre-processing and encoding phases of the proposed method, the RCs of drums percussion lines are represented in duration-weighted notation (DWN). Then, the vector of DWN is encoded to be free of the dimensional dependence on the number of figures in the RC. After that, a network is constructed from the encoded DWN using the method proposed in this paper. We find that the rhythmic patterns of the musical work are related to the formation of communities in the constructed music network. In order to confirm such a finding, three network community detection algorithms are applied: Modularity Optimization algorithm and Louvain algorithm for the disjoint community detection, and Bayesian Non-negative Matrix Factorization algorithm for detecting overlapped communities. Furthermore, a new measure for quantifying the relevance of communities to differentiate types of rhythmic patterns is introduced. The proposed technique has been applied to automatic extraction of rhythmic pattern and rhythmic summarization of the songs of The Beatles, Bob Marley, and other artists, respectively. The results show that the method of extraction and summarization has good performance.

Research paper thumbnail of Dodecaphonic Composer Identification Based On Complex Networks

BRACIS, 2019

In the musical composition process, even subconsciously, it is common for composers to imprint th... more In the musical composition process, even subconsciously, it is common for composers to imprint their personal signature implicitly within the work. This characteristic allows the recognition and the individualization of its origin through the sound assembly. With this in mind, the composer identification through the signature in his works allow us to classify a musical genre into more specific subcategories. However, the characteristics of that signature are of such great variation that make identification task difficult. This paper proposes the use of data mining within complex networks and machine learning techniques to classify a dodecaphonic musical work according to its composer. Considering the dodecaphonic matrix, two types of networks were generated: 1) intervals and 2) series. The feature vector is composed of new melodic topological measures adapted to the calculation from the adjacency matrix and conventional topological measurements. The classifiers Random Forest, AdaBoost and Random Subspace returned high values of accuracy and AUC (> 90%) in the identification of composers Schoenberg, Stravinsky and Webern. Confirming the existence of a relation among the characteristics of the original series, the selection and application of derived series and the composer. The results obtained revealed a good performance and showed that the experiment is very promising.

Research paper thumbnail of Characterization and identification of twelve-tone composers

ENIAC, 2018

The individualism of each composer is shaped in an inherent way to his personality, aiming for re... more The individualism of each composer is shaped in an inherent way to his personality, aiming for recognition of particular form through the own songs. In this way, it is possible to categorize a musical subgenre at a deeper level by identifying the composer from his works. However, the characteristics of each composer are so varied that they are difficult to identify. In this paper it is proposed to use machine learning to classify works of twelve-tone music according to the composer, under the hypothesis that in choosing the twelve-tone series a part of his signature was reflected. Experimental results showed promising performance and confirmed the existence of a relation between composer and series. Resumo. O individualismo de cada compositorécompositor´compositoré plasmado de forma inerente a sua personalidade, visando o seu reconhecimento particular através das suas próprias músicas. Desta forma, ´ e possível categorizar um subgênero musical em um nível mais profundo mediante a identificaçidentificaç˜identificação do compositor a partir das suas obras. No entanto, as características de cada compositor são tão variadas que dificultam sua identificaçidentificaç˜identificação. Neste artigó e proposto usar aprendizado de máquina para classificar obras de música dodecafônica segundo o compositor, sob a hipótese de que na escolha da série dodecafônica ficou refletida uma parte da sua assinatura. Resultados experimentais mostraram desempenho promissor e confirmaram a evidencia da existência de uma relaçrelaç˜relação entre compositor-série. 1. IntroduçIntroduç˜Introdução O crescimento constante dos bancos de dados musicais disponíveis digitalmente tem mo-tivado o desenvolvimento de diferentes métodos de classificaçclassificaç˜classificação automática de música. Tipicamente, tais métodos têm sido direcionados maioritariamente para a classificaçclassificaç˜classificação de gêneros musicais, a qual tem sido abordada desde diferentes perspectivas [1, 14, 17]. Contudo, outros níveis de classificaçclassificaç˜classificação são possíveis, como classificaçclassificaç˜classificação em subgêneros [15] e em estilos [16]. No entanto, após ter classificado determinado banco de dados em algum dos dois anteriores níveis, tambémtambém´tambémétambémé´tambéméútil discriminar cada categoria obtida em uma subcategoria mais profunda, o compositor, deixando-o assim mais organizado e preparado para ser utilizado em outros sistemas, como sistema de recomendaçrecomendaç˜recomendação [13] ou sistemas de análise e extraçextraç˜extração de dados [18], dentre outros. O fundamento principal por trás da tarefa de identificaçidentificaç˜identificação do compositorécompositor´compositoré que um alvo procurado por quase todos os compositores musicaisémusicais´musicaisé impregnar nas suas obras a sua assinatura musical para assim poderem ser reconhecidos através delas. Em muitos casos esse processó e inconsciente, e nasce da essência intrínseca do compositor na sua

Research paper thumbnail of Computer-Aided Music Composition with LSTM Neural Network and Chaotic Inspiration

IJCNN, 2013

In this paper a new neural network system for composition of melodies is proposed. The Long Short... more In this paper a new neural network system for composition of melodies is proposed. The Long Short-Term Memory (LSTM) neural network is adopted as the neural network model. We include an independent melody as an additional input in order to provide an inspiration source to the network. This melody is given by a chaotic composition algorithm and works as an inspiration to the network enhancing the subjective measure of the composed melodies. As the chaotic system we use the Hénon map with two variables, which are mapped to pitch and rhythm. We adopt a measure to conduct the degree of melodiousness (Euler's gradus suavitatis) of the output melody, which is compared with a reference value. Varying a specific parameter of the chaotic system, we can control the complexity of the chaotic melody. The system runs until the degree of melodiousness falls within a predetermined range.

Research paper thumbnail of Musical Scales Recognition via Deterministic Walk in a Graph

BRACIS, 2016

Musical scales play an important role in melodies, since its properties are reflected to the melo... more Musical scales play an important role in melodies, since its properties are reflected to the melodic essence. The extraction and understanding of scales are essential in both analysis and composition of music. However, the scale identification is a nontrivial task. Consequently, classic algorithms for identifying scales have been developed based on the most popular scales, such as major and minor scales. In this paper, we propose a comprehensive method for identifying musical scales, which allows to detect a wide range of scales beyond the traditional ones. Our method uses a deterministic walk through the nodes of a graph, where each node represents a valid interval structure. The transition between nodes is performed following a validation rule that governs the fragmentation of intervals. Moreover, if the scale is incomplete, possible structures can be determined and the scale is estimated according to the harmonic similarity percentage measure. The proposed method has been tested using a database of Finnish folk melodies and a data set of random melodies composed using rarely used scales. Experimental results show good performance of the proposed technique.

Research paper thumbnail of Identification of Music Genres by Using Communities Detection in Complex Networks

ENIAC , 2015

In this paper, we propose a new methodology for identification of musical genres in symbolic data.

Research paper thumbnail of Rhythmic Pattern Extraction by Community Detection in Complex Networks

BRACIS, 2014

In this paper, we study musical knowledge extraction and discrimination. Specifically, we propose... more In this paper, we study musical knowledge extraction and discrimination. Specifically, we propose a method for automatic extraction of drums rhythmic patterns of music and the rhythmic summarization of a set of songs from the same artist. A musical piece is generally formed of one or more predefined rhythmic patterns and such patterns are composed of Rhythmic Cells (RC), which are groups of rhythmic figures derived from n-th division of a larger rhythmic figure. At the pre-processing and encoding phase, the RCs of drums percussion lines are represented in Duration-Weighted Notation (DWN). Then, the vector of DWM is encoded to be free of the dimensional dependence on the number of figures in the RC. After that, a network is constructed from the encoded DWM using the method proposed in this paper. We find that the rhythmic patterns of the musical work are related to the formation of communities in the network. In this work, two community detection algorithms are used: Louvain algorithm for the disjoint community detection and Bayesian Nonnegative Matrix Factorization (BNMF) algorithm for detecting overlapping communities. Moreover, a new measure for quantifying the relevance of communities to differentiate types of rhythmic patterns is introduced. The proposed technique has been applied to automatic extraction of drums rhythmic pattern of the song "Drive my car'' by The Beatles. Experimental results show good performance of the proposed method.

Research paper thumbnail of Characterizing chaotic melodies in automatic music composition

Chaos: An Interdisciplinary Journal of Nonlinear Science, 2010

In this paper, we initially present an algorithm for automatic composition of melodies using chao... more In this paper, we initially present an algorithm for automatic composition of melodies using chaotic dynamical systems. Afterward, we characterize chaotic music in a comprehensive way as comprising three perspectives: musical discrimination, dynamical influence on musical features, and musical perception. With respect to the first perspective, the coherence between generated chaotic melodies (continuous as well as discrete chaotic melodies) and a set of classical reference melodies is characterized by statistical descriptors and melodic measures. The significant differences among the three types of melodies are determined by discriminant analysis. Regarding the second perspective, the influence of dynamical features of chaotic attractors, e.g., Lyapunov exponent, Hurst coefficient, and correlation dimension, on melodic features is determined by canonical correlation analysis. The last perspective is related to perception of originality, complexity, and degree of melodiousness (Euler’s gradus suavitatis) of chaotic and classical melodies by nonparametric statistical tests.

© 2010 American Institute of Physics

Research paper thumbnail of Generation of composed musical structures through recurrent neural networks based on chaotic inspiration

IJCNN, 2011

In this work, an Elman recurrent neural network is used for automatic musical structure compositi... more In this work, an Elman recurrent neural network
is used for automatic musical structure composition based on
the style of a music previously learned during the training
phase. Furthermore, a small fragment of a chaotic melody is
added to the input layer of the neural network as an inspiration
source to attain a greater variability of melodies. The neural
network is trained by using the BPTT (back propagation through
time) algorithm. Some melody measures are also presented for
characterizing the melodies provided by the neural network and
for analyzing the effect obtained by the insertion of chaotic
inspiration in relation to the original melody characteristics.
Specifically, a similarity melodic measure is considered for
contrasting the variability obtained between the learned melody
and each one of the composite melodies by using different
quantities of inspiration musical notes.

Research paper thumbnail of Chaotic Melody Generation and Statistical Characterization - Andrés Coca, Zhao Liang and Gerard Olivar

Dynamics Days South America , 2010

keywords: Applications of Nonlinear Sciences Chaotic Dynamics.

Research paper thumbnail of Controlando melodías caóticas - A. Coca, G. Olivar y Z. Liang

Se presenta el desarrollo de un algoritmo para la composición automática de melodías a partir de ... more Se presenta el desarrollo de un algoritmo para la composición automática de melodías a partir de sistemas dinámicos no lineales (caóticos o no caóticos). Las variables de solución de los sistemas son usadas para la extracción de las variables musicales que constituyen la melodía (altura, ritmo y velocidad). Las variables musicales pueden ser acondicionadas según algunas especificaciones musicales de entrada. Se destaca la posibilidad de crear melodías con escalas microtonales y la facultad de disponer del conjunto total de escalas y modos posibles en el sistema temperado. Las técnicas para el control del caos OGY, TDAS y FPIC son utilizadas independientemente para controlar directamente el sistema caótico e indirectamente la melodía generada. Dependiendo de la estrategia de control empleada, el atractor puede evolucionar a una órbita periódica o a un punto fijo de periodo n. El reflejo musical de esto es la transformación de la melodía en una frase musical repetitiva, un grupo consecutivo de notas (arpegio) o una nota musical sostenida.

Research paper thumbnail of Controlling Chaotic Melodies - A. Coca, G. Olivar and Z. Liang

ENIP, 2009, 2009

This paper presents an algorithm for automatic composition of melodies by using nonlinear dynamic... more This paper presents an algorithm for automatic composition of
melodies by using nonlinear dynamical systems. The variables
of the systems are used for extraction of components that
constitute the musical melody (pitch, rhythm and dynamics)
which can be adjusted according to specific musical input. It
should be highlighted that the proposed algorithm not only can
generate melodies with microtonal scales, but also is capable
of having the whole set of possible scales and modes in the
temperated system. Techniques for control of chaos are used to
transform the chaotic attractor to a periodic or a fixed point
attractor, generating melody of a repeated musical phrase, a
series of consecutive notes (arpeggio) or a sustained musical
note.

Research paper thumbnail of Desarrollo y aplicación de un algoritmo para la distribución de melodías en varias voces 2

Andrés Eduardo Coca S. * Resumen -Se presenta el desarrollo, la implementación y la aplicación de... more Andrés Eduardo Coca S. * Resumen -Se presenta el desarrollo, la implementación y la aplicación de un algoritmo para distribuir las notas de una o varias melodías de forma organizada y sistemática. Se muestran los resultados obtenidos al distribuir las notas de la escala cromática, para crear una ilusión acústica. Esta ilusión es utilizada en la composición automatizada de algunos compases de la obra para cuarteto de cuerdas clásico Pitch Music.

Research paper thumbnail of Algoritmo para la distribucion de melodías en varias voces

Resumen-Se presenta el desarrollo, la implementación y la aplicación de un algoritmo para distrib... more Resumen-Se presenta el desarrollo, la implementación y la aplicación de un algoritmo para distribuir las notas de una o varias melodías de forma organizada y sistemática. Se muestran los resultados obtenidos al distribuir las notas de la escala cromática, para crear una ilusión acústica. Ilusión que es utilizada en la composición automatizada de algunos compases de la obra para cuarteto de cuerdas Op.1 #1 Pitch Music.

Research paper thumbnail of Mineração de estruturas musicais e composição automática utilizando redes complexas - PhD. Thesis, ICMC, USP, 2014

A teoria das redes complexas tem se tornado cada vez mais em uma poderosa teoria computacional ca... more A teoria das redes complexas tem se tornado cada vez mais em uma poderosa teoria computacional capaz de representar, caracterizar e examinar sistemas com estrutura não trivial, revelando características intrínsecas locais e globais que facilitam a compreensão do comportamento e da dinâmica de tais sistemas. Nesta tese são exploradas as vantagens das redes complexas na resolução de problemas relacionados com tarefas do âmbito musical, especificamente, são estudadas três abordagens: reconhecimento de padrões, mineração e síntese de músicas. A primeira abordagem é desempenhada através do desenvolvimento de um método para a extração do padrão rítmico de uma peça musical de caráter popular. Nesse tipo de peças coexistem diferentes espécies de padrões rítmicos, os quais configuram uma hierarquia que é determinada por aspectos funcionais dentro da base rítmica. Os padrões rítmicos principais são caracterizados por sua maior incidência dentro do discurso musical, propriedade que é refletida na formação de comunidades dentro da rede. Técnicas de detecção de comunidades são aplicadas na extração dos padrões rítmicos, e uma medida para diferenciar os padrões principais dos secundários é proposta. Os resultados mostram que a qualidade da extração é sensível ao algoritmo de detecção,
ao modo de representação do ritmo e ao tratamento dado às linhas de percussão na hora de gerar a rede. Uma fase de mineração foi desempenhada usando medidas topológicas sobre a rede obtida após a remoção dos padrões secundários. Técnicas de aprendizado supervisionado e não-supervisionado foram aplicadas para discriminar o gênero musical segundo os atributos calculados na fase de mineração. Os resultados revelam a eficiência da metodologia proposta, a qual foi constatada através de um teste de significância estatística. A última abordagem foi tratada mediante o desenvolvimento de modelos para a composição de melodias através de duas perspectivas, na primeira perspectiva é usada uma caminhada controlada por critérios sobre redes complexas predefinidas e na segunda redes neurais recorrentes e sistemas dinâmicos caóticos. Nesta última perspectiva, o modelo é treinado para compor uma melodia com um valor preestabelecido de alguma característica tonal subjetiva através de uma estratégia de controle proporcional que modifica a complexidade de uma melodia caótica, melodia que atua como entrada de inspiração da rede.

Research paper thumbnail of Composición automática de fragmentos musicales mediante sistemas dinámicos caóticos y bifurcaciones - Master thesis, UNAL, 2009.

Research paper thumbnail of Estimación del pitch en senales monofónicas de voz cantada - Bachelor thesis, UNAL, 2004

Objetivos IX Glosario X algoritmo, se estudian algunos parámetros acústicos de la voz y las princ... more Objetivos IX Glosario X algoritmo, se estudian algunos parámetros acústicos de la voz y las principales características de la voz cantada.

Research paper thumbnail of Composición algorítmica de melodías estocásticas basadas en la inflexión sobre un ritmo dado - Bachelor Thesis, UCaldas, 2008.

Research paper thumbnail of 13. Protótipo para o ensino de controle digital através de um sistema de controle de temperatura - Mina, 2023

Esta licença permite remixe, adaptação e criação a partir do trabalho, para fins não comerciais, ... more Esta licença permite remixe, adaptação e criação a partir do trabalho, para fins não comerciais, desde que sejam atribuídos créditos ao(s) autor(es). Conteúdos elaborados por terceiros, citados e referenciados nesta obra não são cobertos pela licença.

Research paper thumbnail of 12. Desenvolvimento de um módulo didático para o ensino de controle de sistemas baseado no sistema de levitação magnética - Escher, 2022

As atividades práticas auxiliam o aprendizado do aluno, ajudando-o a visualizar a teoria de uma f... more As atividades práticas auxiliam o aprendizado do aluno, ajudando-o a visualizar a teoria de uma forma mais objetiva e experimental, o que facilita mais a compreensão do assunto estudado. Uma ferramenta que une a teoria com a prática é o módulo didático, entretanto, seus altos custos e sua baixa adaptabilidade dificultam sua empregabilidade. Desta forma, a construção de módulos didáticos de baixo custo e de fácil modificação se fazem necessários. Consequentemente, alguns módulos didáticos têm sido propostos, dentre estes destaca-se o sistema de levitação eólica desenvolvido por Medeiros (2019), o qual consiste em manter a altura de uma esfera em uma posição desejada mediante a injeção de um jato de ar na base. Neste contexto, foi criado uma ferramenta didática para o ensino de controle de sistemas baseado no campo magnético, que facilita o aprendizado, apresentando um baixo custo de construção e facilita a adaptabilidade. O sistema possuí um controlador PID digital, programado em Arduino, responsável por controlar a corrente do eletroímã, que é o responsável por gerar o campo magnético e variar a intensidade do fluxo de campo necessário para atrair o núcleo ferro magnético no interior da solenoide, permitindo controlar a posição em que este ficará no interior deste. O atuador da planta é um eletroímã, enquanto que a posição do núcleo é verificada com um sensor fototransistor. Para aumentar a didática, a ferramenta tem uma interface gráfica para a alteração de parâmetros, permitindo observar suas consequências na resposta do sistema de forma guiada e intuitiva. O projeto mostrou um bom desempenho com baixo custo, apresentando um interface que permite alterar os parâmetros do controlador PID digital e demonstrar a resposta do sistema.

Research paper thumbnail of 11. Desenvolvimento de um theremin óptico digital com síntese de áudio e interface gráfica - Ramos, 2021

The Theremin, in addition to being one of the first electronic musical instruments, has the parti... more The Theremin, in addition to being one of the first electronic musical instruments, has the particularity of not requiring physical contact to perform it, since, to do so, it is only necessary to bring your hands closer or farther away from the instrument's antennas, in which the antenna positioned on the right controls the frequency and the left controls its loudness. Given this, Gomes et al. (2009) developed a Theremin with ultrasonic sensors, using a DSP to map the distance of the hands about the sensors, applying an FM synthesis to generate the sound, and even relating colors to musical notes through Emitting Diodes of Light (LEDs) Red-Green-Blue (RGB). In this project, an optical digital Theremin with a graphical interface was developed, with good cost-effectiveness, timbre diversity, and ease of interaction. For this, two optical sensors were used, responsible for measuring the distance about the instrument. Through a microcontroller, the captured data is processed and sent via the serial port; then, from a PC, the subtractive synthesis method is applied to generate and modify the instrument's timbre. In addition, a graphical interface was developed to allow the visualization of the instrument's parameters, as well as providing options for its configuration. After completion of the prototype, experiments were carried out to verify the distance-frequency relationship, timbre diversity, and cost analysis, for which the prototype had a low relative error for the distance-frequency relationship, ability to create different timbres, and relationship high-cost benefit. Finally, a demonstration of the prototype was also presented through the execution of two musical pieces. With this, it was verified that the instrument can be used by beginner musicians in the introduction to musicalization and the development of musical perception, and also by professional musicians in recordings and presentations.

Research paper thumbnail of 10. Ensinando probabilidade com o jogo de dados de Mozart - Djones, 2021

Com a conclusão deste trabalho, gostaria de agradecer a todos que nele contribuíram eàs pessoas q... more Com a conclusão deste trabalho, gostaria de agradecer a todos que nele contribuíram eàs pessoas que fizeram a diferença em todos os dias de minha vida. De perto ou de longe, recebam meu sincero obrigado! A minha família e aos meus amigos, por todo amparo e motivação que me deram. Aos meus professores e colegas, com os quais muito aprendi nessa jornada. Aos professores que cederam seu tempo e suas turmas. Com muito profissionalismo contribuíram nesta pesquisa. Aos meus orientadores, pela sabedoria, disponibilidade, paciência, correções e sugestões. Também desejo transmitir meus agradecimentosà Universidade Tecnológica Federal do Paraná, pelo ensino de qualidade que supre aos seus acadêmicos e pela concessão de uma bolsa de estudos.

Research paper thumbnail of 9. Desenvolvimento de um conjunto didático para o ensino de controle baseado no sistema pêndulo-hélice - Fukumoto, 2020

Research paper thumbnail of 8. Desenvolvimento de uma ferramenta didática para o ensino de controle baseada no sistema de pêndulo invertido sobre barra deslizante - Calliari, 2020

Research paper thumbnail of 7. Estudo comparativo de métodos avançados de controle implementados no sistema bola e barra - Prunzel, 2019

The choice of suitable control methods for process regulation is fundamental in the engineering f... more The choice of suitable control methods for process regulation is fundamental in the engineering field, as it helps to define which one is the best according to several criteria, aiming to obtain better results. However, such a comparison is not always easy and straightforward, as it is necessary for the previous implementation of the different methods to compare and the subsequent analytical examination of the obtained data. Thus, in the control area, a comparison between different controller specific design methods becomes necessary. To this end, some research has been developed, such as the comparative study of PID, I-PD, and PD-PI controllers through various performance indexes proposed by Sain (2016). In the present work, advanced digital control algorithms were implemented and the respective comparative study according to different performance specifications, with which we obtained a methodology capable of assisting the designer in choosing the best control method. For this, the ball and beam system already implemented was chosen, which was controlled and compared with different control methods, such as fuzzy logic (FL), artificial neural networks (ANN), and a PID controller with a derivative filter (PID N). The unstable ball and beam system is regulated and supervised employing a previously elaborated software but with some updates introduced, where the user can define the control method to be used before the newly implemented methods, as well as some parameters. Thus, the comparison was performed following statistical guidelines (MANOVA) for the various error-based measures, namely the IAE, ISE, ITAE, and ITSE, establishing the modified PID as the best control strategy for the ball and beam plant at the significance level of 95%. Improving the study prototype will enable future students to learn advanced controllers, as well as their differences and characteristics.

Research paper thumbnail of 6. Harmonização musical automática baseada em redes neurais artificiais - Costa, 2019

Em termos musicais, harmonia define-se como a arte de combinar diversas notas musicais simultanea... more Em termos musicais, harmonia define-se como a arte de combinar diversas notas musicais simultaneamente de forma a criar um som coerente aos ouvidos humanos, com objetivo de acompanhar, emoldurar e preencher. Todavia, a elaboração de uma harmonia para determinada melodia não é uma tarefa trivial, uma vez que requer conhecimento e experiência musical, além de intenso estudo da área de teoria musical, algo que demanda tempo, podendo até levar anos para alcançar habilidades razoáveis. Sendo assim, faz-se benéfico e proveitoso o desenvolvimento de um sistema capaz de harmonizar automaticamente melodias. Esforços e tentativas vêm sendo realizadas na solução do problema de harmonias, conforme o método proposto por Koops, Magalhães e Haas (2013), o qual gera acordes para cada nota de uma melodia dada e seleciona a melhor sequência, combinando-a à melodia de entrada em um único arquivo de saída. No presente projeto, foi proposta a construção de uma ferramenta para a harmonização de melodias predefinidas usando técnicas de inteligência artificial para obter resultados que sejam realistas, coerentes com as regras da teoria da harmonia e que apresentem diversidade. Dessarte, uma melodia definida com dados musicais simbólicos e devidamente processada serve de entrada para uma rede neural artificial que gera para esta acordes, tendo sido treinada com base em um banco de dados de músicas contendo melodia e harmonia. A saída do sistema é a sequência de acordes a ser aplicada à melodia. Em virtude da complexidade de obtenção e análise de resultados, testes quantitativos e qualitativos foram realizados, utilizando desde medidas de performance calculadas a partir de matrizes de confusão até pesquisa de enquete online com exposição da opinião de participantes voluntários anônimos. Ao final, pode-se concluir que o sistema foi capaz de gerar harmonias alinhadas com os objetivos.

Research paper thumbnail of 5. Desenvolvimento de uma ferramenta educacional para o ensino da teoria de controle baseada na levitação eólica -Silveira, 2019

MEDEIROS, Daniella Silveira. Development of an educational tool for the teaching of control theor... more MEDEIROS, Daniella Silveira. Development of an educational tool for the teaching of control theory based on the wind levitation. 2019.

Research paper thumbnail of 4. Desenvolvimento de um protótipo de identificação das linhas de ônibus no transporte coletivo - Dos Anjos, 2018

A Microeletrônicaé umaárea da Engenharia em acensão, que associadaà inclusão social possibilita a... more A Microeletrônicaé umaárea da Engenharia em acensão, que associadaà inclusão social possibilita a construção de aparelhos de baixo custo, afim de proporcionar mais conforto, e trazer melhorias para o cotidiano das pessoas com necessidades especiais. A maioria das cidades brasileiras não oferecem serviço especializado na identificação de transporte público para pessoas que possuem debilidades na visão. Portanto, um sistema eletrônico para identificar linhas deônibus intensifica a inclusão social e permite que o usuário tenha mais segurança e autonomia na hora de embarcar em umônibus. Por exemplo, em João Pessoa-PB, um grupo de estudantes construíram um aparelho de uso individual, que faz o motorista deônibus estar ciente que há um deficiente visual em um determinado ponto, também em Natal-RN a prefeitura instalou placas em braile nas plataformas com as linhas que operam naquele local. Neste trabalhoé apresentado uma proposta para identificação de linhas deônibus de uso coletivo. O principal objetivoé a interação direta com os passageiros que necessitam do serviço de identificação doônibus. O sistema possui dois aparelhos, um instalado noônibus e outro no ponto de embarque. A identificação se dá por meio dé audio em auto falantes, informando aos passageiros, no ponto, o nome da linha dô onibus que se aproxima. O sistema se comunica entre si por meio de antenas de radio frequencia, cada aparelho recebe um microcontrolador, programado para controlar o fluxo de informação entreônibus e ponto de embarque. A linha de umônibusé anunciada no momento em que oônibus se aproxima do ponto, em seguida esta mesma linhaé ignorada, por um determinado tempo para evitar o tráfego de informações repetidas. O sistema foi testado com carro de passeio para medir o alcance das antenas, bem como a funcionalidade do programa. O programa correspondeu com as exigências do projeto, porém as antenas não atenderamàs especificações de alcance do fabricante. Pode-se obter um alcance maior de comunicação entre os sistemas, substituindo as antenas por outros modelos em que as configurações seja de fácil adaptação no código fonte, contudo, o sistema funcionou com boa qualidade deáudio e sem repetições.

Research paper thumbnail of 3. Desenvolvimento de um sistema de controle digital para afinação de instrumentos de corda - Valério, 2018

The acoustic quality performance of an musical instrument is related to its correct tuning. Howev... more The acoustic quality performance of an musical instrument is related to its correct tuning. However, the tuning of string musical instruments varies over time due to environmental and natural factors. Therefore, the musician must constantly check the tuning, which requires technical knowledge and time. Thus, the development of an automatic tuning system for string instruments had become necessary. Some commercial devices that ensure automatic tuning can be easily found in the market, for example TronicalTune and RoadieTuner, althought, they are not popular due to elevated price. In this project, an automatic tuning control system for acoustic string instrument was developed with accuracy, rapidity and low cost. Such system has a metal piece that fits on the tunning machine and by a software the user chooses the desired frequency for the chosen string. A microphone captures the acoustic signal produced by the string; after that, an analog input of the Arduino UNO reads that signal and by an autocorrelation algorithm estimates the fundamental frequency of the audio sample. Besides that, the Arduino is responsible for determining the difference between the frequency of the received signal and the frequency of the desired musical note. Two digital controls, PID and another one based on the system equation (obtained through a mathematical modeling), were implemented in the Arduino to calculate and send to the stepper motor the signal that sets the direction of rotation, stretching or loosening the string, and the amount of steps required for the string to be tuned. Experiments were performed using a ukulele, obtaining satisfactory results in time and accuracy. The system can be used by both beginner and advanced musicians and minimizes tuning time.

Research paper thumbnail of 2. Projeto e implementação de um aparato para estudo e pesquisa em controle com base no sistema bola e barra - Camargo, 2018

CAMARGO, Claudinei Veríssimo de. Design and implementation of an apparatus for study and research... more CAMARGO, Claudinei Veríssimo de. Design and implementation of an apparatus for study and research in control based on the ball and beam system. 2018. 178p. Graduation Course (Bachelor's Degree in Electronic Engineering),

Research paper thumbnail of 1. Máquina para mistura de pigmentos através do modelo CMYK com interface LCD sensível ao toque - Ludwig - 2016

Color is a very important feature due to the meaning and implicit information they provide to obj... more Color is a very important feature due to the meaning and implicit information they provide to objects of day by day. Because of this, the process of creating composite colors is a widely used task in the industry, but such a process requires the exact dosing of primary color pigments, which is costly and has limitations in the amount of colors offered. In this way, developing a machine to create specific pigment paints with quality colors and consistently is of great use. Nowadays it is possible to find commercial inkmetric machines capable of performing pigment dosages to create new colors, for example, the COROB machine allows the use of 16 dyes with volume and sequential dosage, however, at a very high cost. Therefore, in this work, a machine capable of calculating, measuring and dosing pigments was designed and developed in order to perform dosages for the mixing of different primary color pigments in order to obtain composite colors with a big variety, with low cost and for different quantities of ink chosen. The DMTCP has a touch-sensitive liquid crystal display (TFTLCD) that facilitates its handling through predefined or new colors, and allows the exact amount of ink desired. In order to test the homogeneity of the colors, the statistical analysis of multivariate analysis of variance (MANOVA) was applied, which allowed to conclude at two different levels of significance that there is no statistically significant difference between the mixed colors for different samples.

Research paper thumbnail of Museu da computação: A preservação da evolução tecnológica

IV Congresso Brasileiro Interdisciplinar em Ciência e Tecnologia (CoBICET), 2023

Research paper thumbnail of Museu das grandes novidades: A preservação da memória da evolução da computação

Workshop de Ciência, Tecnologia e Inovação (WCTI), 2023

Research paper thumbnail of Desenvolvimento de um Instrumento Digital para o Tratamento da Artrite

SICITE, 2023

Define-se como artrite reumatóide uma doença crônica autoimune incurável, cujo grau de risco vari... more Define-se como artrite reumatóide uma doença crônica autoimune incurável, cujo grau de risco varia entre pacientes. Apesar de incurável, existem tratamentos que incluem medicação e/ou fisioterapia para mitigação das dores e seu avanço. Contudo, os tratamentos fisioterapêuticos, devido a sua natureza repetitiva, podem ser desmotivantes aos pacientes. A musicoterapia pode ser uma alternativa para aumentar a adesão aos tratamentos e se mostra promissora na redução de dores e estresse. Assim, neste trabalho foi iniciado o desenvolvimento um instrumento digital musical programável para o auxílio no tratamento de artrite. O instrumento é operado pelo paciente mediante o movimento das mãos sobre um aparelho flexor, cuja pressão aplicada é mensurada por um sensor RP-C18.3-ST e utilizada para o controle de frequência na etapa de síntese. Foi utilizado um microcontrolador para a síntese sonora subrativa, devido a sua natureza de fácil programação. A resposta temporal desse instrumento foi analisada, mostrando que a síntese ocorreu da maneira esperada. Os resultados obtidos são promissores e espera-se que futuramente o sistema aqui desenvolvido possa ser utilizado para tratar pacientes reais.

Research paper thumbnail of TherEMGin: desenvolvimento de um theremin controlado por sinais eletromiográficos (EMG)

SICITE 23, 2023

Embora a música seja universal entre os humanos, o mesmo não pode ser dito com relação a ser músi... more Embora a música seja universal entre os humanos, o mesmo não pode ser dito com relação a ser músico, já que os instrumentos musicais geralmente requerem uma coordenação motora precisa, especialmente nas mãos, então, para aqueles que sofrem com limitações na movimentação do membro, acaba sendo quase impossível tocar um instrumento. O Theremin é um caso especial, pois embora sua interpretação não obrigue nenhum toque físico no aparelho, ainda é preciso ter movimentos extremamente precisos com os dedos para executar uma nota musical da maneira mais estável possível. O presente artigo propõe uma adaptação do Theremin Óptico Digital para que seja controlado utilizando sinais eletromiográficos (EMG). Primeiramente foi projetado um modelo para o mapeamento das notas musicais naturais, considerando uma oitava como referência, obtendo como resultado a equação que relaciona o ângulo do movimento com a frequência. Depois, foi preciso pré-processar o sinal EMG, filtrá-lo e obter um sinal médio, interpretando-o como controle de amplitude do som. Espera-se que o aparelho possa ser utilizado para tratamentos medicinais e ensino musical para pessoas com doenças neuromusculares.

Research paper thumbnail of Arquitetura para a classificação automática de gêneros musicais utilizando análise de imagens e redes complexas

SICITE, 2023

Hodiernamente a música é amplamente consumida por meios digitais, como plataformas de streaming. ... more Hodiernamente a música é amplamente consumida por meios digitais, como plataformas de streaming. Nesse contexto, a classificação de gêneros musicais tem papel vital, pois permite a criação de sistemas de recomendação de música e a organização de grandes bancos de dados musicais. Entretanto, tais tarefas se mostram desafiadoras e tediosas devido ao alto grau de complexidade e repetição. Desta forma, convém o desenvolvimento de sistemas computacionais capazes de realizar a classificação de músicas de acordo com o gênero de forma automática, acurada e eficiente. Diante do exposto, o presente artigo propõe uma arquitetura para a classificação de gêneros musicais usando espectrogramas, texturas de imagens e redes complexas. Ainda, foram desenvolvidos programas para a geração de espectrogramas a partir de arquivos de áudio, bem como das características texturais das imagens obtidas, criação de redes complexas e sua respectiva mineração com medidas topológicas. Além disso, um classificador baseado em redes neurais foi implementado para avaliar a desempenho do sistema, para o qual os resultados demonstraram performance razoável no conjunto de teste.

Research paper thumbnail of Criação de dispositivo para facilitar a percepção musical por pessoas com surdez por meio de estímulos táteis

SICITE, 2023

A música é uma forma rica de expressão composta por diversos elementos, onde a melodia desempenha... more A música é uma forma rica de expressão composta por diversos elementos, onde a melodia desempenha um papel fundamental na apreciação musical e na coordenação de músicos em grupos. No entanto, a falta de dispositivos voltados para indivíduos com surdez total tem sido um obstáculo para que eles apreciem e participem plenamente. Para resolver essa lacuna, surge a necessidade de desenvolver um dispositivo que traduza a melodia em sensações táteis, tornando a musica acessível. Uma abordagem promissora é adotada pela empresa Tron Robótica, que utiliza vibrações emitidas por um alto-falante. No âmbito desse projeto, a proposta é criar um aparelho eletrônico ergonômico e compreensível que capture o sinal acústico de um dispositivo móvel. Esse sinal foi processado para identificar os elementos melódicos, transmitido via Bluetooth para uma placa Raspberry Pi e filtrado para identificar notas e durações. Os dados resultantes são associados a símbolos familiares, como o código Braille musical, e transmitidos para um motor de vibração na mão do usuário. Além disso, uma interface proporciona uma visão em tempo real do processo. Essa iniciativa busca possibilitar que pessoas com surdez total explorem o mundo da música, interpretando melodias e integrando-se em grupos musicais, promovendo assim a inclusão musical.

Research paper thumbnail of Seleção de mapas caóticos e estratégia de controle para a composição automática de melodias

SICITE, 2020

Um importante elemento em toda obra musical é a melodia, a qual contém características subjetivas... more Um importante elemento em toda obra musical é a melodia, a qual contém características subjetivas intrínsecas que lhe permitem transmitir emotividade e sentimentos à peça. No entanto, compor uma melodia com um valor preestabelecido para alguma dessas características é um grande desafio composicional. Uma tentativa para abordar esse problema é o algoritmo de composição proposto por Coca et al. (2013), o qual compõe melodias com valores predefinidos na característica de melodiosidade melódica através de um controlador proporcional, uma rede Long-Short-Term Memory (LSTM) e um sistema caótico. Visando aprimorar a abrangência desse algoritmo, no presente artigo é apresentado o estudo e a seleção de outros sistemas caóticos discretos e com diferentes dimensões; bem como outra medida subjetiva, a originalidade melódica. Além disso, foram testados outros controladores digitais. Os resultados obtidos foram satisfatórios. Nesse meandro, espera-se proporcionar ideias e sementes musicais de cunho teórico fomentada pelo compositor artificial.

Research paper thumbnail of ENDICT 2019 - Resumos

ENCONTRO DE INICIAÇÃO CIENTÍFICA DA UTFPR (ENDICT), 2019

1. Composição automática de linhas de percussão usando redes complexas e células rítmicas - Eduar... more 1. Composição automática de linhas de percussão usando redes complexas e células rítmicas - Eduarda R. Dalazoana e Andrés E. C. Salazar

2. Composição automática de melodias com característica melódica subjetiva predefinida
baseada em sistemas caóticos, redes LSTM e estratégias de controle automático
Jordano V. Lahm e Andrés E. C. Salazar

3. Geração automáticas de melodias gospel através de regras
Thais M. S. Batista1 e Andrés E. C. Salazar

Research paper thumbnail of Análise de composições dodecafônicas para obtenção de características descritivas

ENDICT, 2016

Para a construção de uma obra musical, regras devem ser seguidas de acordo com diferentes métodos... more Para a construção de uma obra musical, regras devem ser seguidas de acordo com diferentes métodos composicionais, sendo o dodecafonismo um destes. No dodecafonismo, o compositor seleciona uma série de notas sem repetição, chamada série original P0 e, a partir desta, elabora a chamada matriz serial, que serve de regra para a composição da obra. Entretanto, a escolha de uma série adequada mostrase por muitas vezes uma tarefa bastante complicada, já que as possibilidades de seleção se estendem por 12! (fatorial) opções diferentes, gerando a busca por um meio de seleção melhor, que disponha de boas qualidades. É fácil encontrar diversos meios disponíveis que geram a matriz serial, no entanto o desenvolvimento de ferramentas para este método composicional não vai além da singela construção da matriz. Para isso, fez-se preciso a implementação de algoritmos capazes da análise das séries P0 de compositores contemporâneos, buscando suas características e tendo por objetivo a concepção de novas séries com características similares às dos compositores, sendo estas apropriadas à dodecafonia. O desenvolvimento tem início com um algoritmo para gerar a matriz serial e, a partir dela, gerar melodias. Com um banco de dados de séries famosas, a análise se dá usando descritores estatísticos, como por exemplo: variedade tonal, dissonâncias, centro tonal, intensidade do clímax, perfis melódicos, etc., e a partir dos resultados, encontrar novas séries com valores similares aos obtidos e compor melodias com estas séries, avaliando posteriormente as melodias compostas. Desta maneira, foi possível obter boas melodias com resultados razoáveis, dentro das análises em questão, além de possibilitar o desenvolvimento da área composicional do dodecafonismo, permitindo maior compreensão para a escolha de séries melódicas através de um método quantitativo. Se baseando nestes resultados, se propõe o desenvolvimento, como trabalho futuro, de um método para encontrar novas séries com características adequadas de forma automática.

Research paper thumbnail of MUSIQUE ALGORITHMIQUE: Systèmes dynamiques chaotiques, réseaux de neurones artificiels récurrents et réseaux complexes

Palestra no INRIA. Université de Rennes 1, França. 2012

Research paper thumbnail of Seducción Oriental - Poema sinfónico - 2006

Para banda sinfónica 2006

Research paper thumbnail of Pitch Music - String quartet - 2004

Obra para cuarteto de cuerdas clásico 2004

Research paper thumbnail of Dodecaphonic Composer Identification Based On Complex Networks

2019 8th Brazilian Conference on Intelligent Systems (BRACIS), 2019

In the musical composition process, even subconsciously, it is common for composers to imprint th... more In the musical composition process, even subconsciously, it is common for composers to imprint their personal signature implicitly within the work. This characteristic allows the recognition and the individualization of its origin through the sound assembly. With this in mind, the composer identification through the signature in his works allow us to classify a musical genre into more specific subcategories. However, the characteristics of that signature are of such great variation that make identification task difficult. This paper proposes the use of data mining within complex networks and machine learning techniques to classify a dodecaphonic musical work according to its composer. Considering the dodecaphonic matrix, two types of networks were generated: 1) intervals and 2) series. The feature vector is composed of new melodic topological measures adapted to the calculation from the adjacency matrix and conventional topological measurements. The classifiers Random Forest, AdaBoost and Random Subspace returned high values of accuracy and AUC (> 90%) in the identification of composers Schoenberg, Stravinsky and Webern. Confirming the existence of a relation among the characteristics of the original series, the selection and application of derived series and the composer. The results obtained revealed a good performance and showed that the experiment is very promising.