Interactive music composition system

Unehara, Muneyuki; Onisawa, Takehisa

doi:10.1109/icsmc.2002.1175630

Cited by 6 publications

(3 citation statements)

References 2 publications

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“…For the music field, there have been a lot of researches with IGA too [11]. From these researches, IGA is found to be useful method to reflect human sensibility to create some music better than GA [12], [13].…”

Section: Interactive Genetic Algorithmmentioning

confidence: 99%

Design of Sign Sounds using an Interactive Genetic Algorithm

Miki

Orita

Wake

et al. 2006

2006 IEEE International Conference on Systems, Man and Cybernetics

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In recent years, many kinds of sign sounds have come into use in our daily life. The purpose of sign sounds is to communicate a message. However the ease of message understanding and listening comfort have rarely been taken into consideration. Because people have different tastes and attach a different "image" to sign sounds according to their individual sensibility, it is important for each person to be able to make melodies freely and easily, and customize sign sounds. We propose a sign sounds design system using an Interactive Genetic Algorithm (IGA). The proposed system produces a melody of two bars based on this IGA. A melody is considered to be a sort of "organism," whose chromosome consists of genes indicating the length, pitch, and velocity of the notes of the melody. Experimental results showed that this system is effective for generating sign sounds. In creating auditory signals, it was found that the method of evolving part-by-part is better than the method of evolving the whole two bars.

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Section: Interactive Genetic Algorithmmentioning

confidence: 99%

Design of Sign Sounds using an Interactive Genetic Algorithm

Miki

Orita

Wake

et al. 2006

2006 IEEE International Conference on Systems, Man and Cybernetics

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“…In the general voting method, 10 points are given to the individual with most votes. For the under-place individual, the evaluation points are calculated using Equation (6). Explicitly, Where X 1 is the evaluation points of individual of order above from one individual from which evaluation points are requested, X 2 is requested evaluation points, Y 1 is the number of evaluation agent votes of X 1 , and Y 2 is the number of evaluation agent votes of X 2 .…”

Section: Side-by-sside Testmentioning

confidence: 99%

“…The IEC system includes various voice generation support and image generation systems [1][2][3][4][5][6][7][8][9][10][11][12]. However, many IEC systems evaluate the solution using only a single person.…”

Section: Introductionmentioning

confidence: 99%

Tournament Evaluation System Considering Multiple People's Kansei Evaluation

Takenouchi

Tokumaru

Muranaka

2010

Kansei Engineering International Journal

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Abstract:We propose an interactive genetic algorithm (IGA) that evaluates individuals from among many people. This technique is effective for consensus building and in bringing together many opinions for applications such as enabling multiple people to design clothes together. With an IGA in which multiple people participate, a simple and easy evaluation interface is required. Our interface technique determines the solution group of the IGA using the tournament type evaluation. In this technique, two solution candidates are presented to evaluators who votes for the best solution candidate. Several evaluators judge the solution candidate's superiority or inferiority, thus deciding the relative rank of the two solutions. Evaluation points for all solution candidates are assigned depending on the relative value of the rank of the two solutions, which is based in turn on the results of the tournament competition. The solution obtained reflects the opinion of all evaluators accurately. In this study, the effectiveness of the proposed technique is verified using a simulation that employs multiple numerical evaluation agents instead of human evaluators. For each tournament competition, the results saturate when 60% of all evaluation agents participate in a vote; that is, the result is unaffected even if more evaluation agents participate. This means that the evaluator load can be reduced by 40%. Moreover, we compare the proposed technique with a general voting method that uses several evaluators voting for the first good individual from among all solution candidates in a displayed list. We confirm that the proposed technique is more effective than the general voting method, because many participants are satisfied.

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Computer Aided Composition System with Interactive Selective Population Climbing

Hasui

2009

2009 WRI World Congress on Computer Science and Information Engineering

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Interactive music composition system

Cited by 6 publications

References 2 publications

Design of Sign Sounds using an Interactive Genetic Algorithm

Design of Sign Sounds using an Interactive Genetic Algorithm

Tournament Evaluation System Considering Multiple People's Kansei Evaluation

Computer Aided Composition System with Interactive Selective Population Climbing

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