Development of an Automatic Emotional Music Accompaniment System by Fuzzy Logic and Adaptive Partition Evolutionary Genetic Algorithm

Kuo, Ping‐Huan; Li, Tzuu-Hseng S.; Ho, Yen-Hung; Lin, Chin‐Tarng

doi:10.1109/access.2015.2443985

Cited by 27 publications

(17 citation statements)

References 33 publications

(30 reference statements)

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“…Additionally, the set of produced pitches are translated into tones belonging to a previously determined musical scale. Kuo et al (2015) created a real-time emotion-based music accompaniment system through a fuzzy logic tempo controller, and an additional genetic evolutionary melody generation system. Harmonic chord progressions were generated using known music theory rules.…”

Section: Musical Composition and Generationmentioning

confidence: 99%

Creating Music With Fuzzy Logic

Cádiz

2020

Front. Artif. Intell.

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Fuzzy logic is an artificial intelligence technique that has applications in many areas, due to its importance in handling uncertain inputs. Despite the great recent success of other branches of AI, such as deep neural networks, fuzzy logic is still a very powerful machine learning technique, based on expert reasoning, that can be of help in many areas of musical creativity, such as composing music, synthesizing sounds, gestural mappings in electronic instruments, parametric control of sound synthesis, audiovisual content generation or sonification. We propose that fuzzy logic is a very suitable framework for thinking and operating not only with sound and acoustic signals but also with symbolic representations of music. In this article, we discuss the application of fuzzy logic ideas to music, introduce the Fuzzy Logic Control Toolkit, a set of tools to use fuzzy logic inside the MaxMSP real-time sound synthesis environment, and show how some fuzzy logic concepts can be used and incorporated into fields, such as algorithmic composition, sound synthesis and parametric control of computer music. Finally, we discuss the composition of Incerta, an acousmatic multichannel composition as a concrete example of the application of fuzzy concepts to musical creation.

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Section: Musical Composition and Generationmentioning

confidence: 99%

Creating Music With Fuzzy Logic

Cádiz

2020

Front. Artif. Intell.

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“…however, this doesn't mean that node 2 is the initial node with the highest influence on node 9, as has been shown. The actual internodal weight between node i and node j, W ij , can be computed according to the formula: (5) where:…”

Section: E Total Weight Between Nodesmentioning

confidence: 99%

“…FL and fuzzy logic systems (FLS) have been extensively used in many different fields of science in general, and industry specifically, with many different purposes, see, for instance, [5]- [11].…”

Section: Introductionmentioning

confidence: 99%

Visualization and Interpretation Tool for Expert Systems Based on Fuzzy Cognitive Maps

et al. 2019

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This paper presents a python library that includes a toolkit with the aim of improving the interpretability of expert systems based on fuzzy cognitive maps through improvements in the visualization and representation of the graphs that can be drawn using the variables of the resulting models. The motivation for the development of the library arises from the need to improve the interpretability of the aforementioned expert systems, given that their multilayer and extracted from experts' knowledge nature can make them very difficult to interpret even for the expert user. Throughout the paper, the reader will be introduced to the basic features of fuzzy logic and fuzzy cognitive maps, and the different developed tools will be defined and exemplified.

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“…Evolutionary algorithm (EA) is a kind of iterative algorithm based on population evolution with heuristic rules, which is inspired by biological evolution and swarm intelligence [1], [12]. As EAs have simple concept and are easy to understand and implement [10], they have developed rapidly in recent years and have dominated in multiple optimization fields [13]- [16], especially with great success in solving NP-hard optimization problems [17]- [19].…”

Section: Introductionmentioning

confidence: 99%

A Distributed Multiple Populations Framework for Evolutionary Algorithm in Solving Dynamic Optimization Problems

et al. 2019

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Aiming to dynamic optimization problems (DOPs), this paper develops a novel general distributed multiple populations (DMP) framework for evolutionary algorithms (EAs). DMP employs six strategies designed in three levels (i.e., population-level, subpopulation-level, and individual-level) to deal with different kinds of DOPs. First, the population-level subpopulation division estimation strategy in initialization phase rationally divides the whole population into several subpopulations to explore distinct subareas of search space sufficiently. Then, during the steady evolutionary process, diversity preservation in individual-level and population-level accelerates the responsiveness of the whole population to a new landscape, while subpopulation-level self-learning of elitist individuals promotes the exploitation of promising areas. Moreover, in subpopulation-level, the archive quality assurance technique avoids repeat exploring the same peaks by storing the locations of different peaks with low redundancy. When landscape variation occurs, in population-level, historical information containing excellent evolutionary pattern is recorded to guide the population evolution better in the new environment. DMP framework is easy to implement in various EAs due to its well generality and independence about operators and parameters of the embedded algorithm. Four DMP-EAs are accomplished in this paper whose basic algorithms are particle swarm optimization (PSO) and differential evolution (DE) with different settings. The performance of the four proposed DMP-EAs is evaluated on all the widely used complex DOP benchmarks from CEC 2009. The testing results indicate that the DMP-EAs generally significantly outperform many state-of-the-art dynamic EAs (DEAs) on most of DOP benchmarks.INDEX TERMS Dynamic optimization problem (DOP), distributed multiple population (DMP) framework, multi-level diversity preservation, adaptive historical information utilization, dynamic evolutionary algorithm (DEA)

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Development of an Automatic Emotional Music Accompaniment System by Fuzzy Logic and Adaptive Partition Evolutionary Genetic Algorithm

Cited by 27 publications

References 33 publications

Creating Music With Fuzzy Logic

Creating Music With Fuzzy Logic

Visualization and Interpretation Tool for Expert Systems Based on Fuzzy Cognitive Maps

A Distributed Multiple Populations Framework for Evolutionary Algorithm in Solving Dynamic Optimization Problems

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