Inspiring Viewers of Abstract Painting by a Gaze Based Music Generation

2014 ◽  
pp. 213-217
Author(s):  
Tatsuya Ogusu ◽  
Jun Ohya ◽  
Jun Kurumisawa ◽  
Shunichi Yonemura
Keyword(s):  
Abstract Painting ◽  
Music Generation

Automatic Music Generation

2019 ◽  
Vol 7 (3) ◽  
pp. 80-82
Author(s):  
Lawakesh Patel ◽  
Nidhi Singh ◽  
Rizwan Khan
Keyword(s):  
Music Generation ◽  
Automatic Music Generation

Polyphonic Music Generation

2020 ◽  
Author(s):  
Vineet Tiwari ◽  
Pratheesh Shivaprasad ◽  
Rushikesh Rushikesh
Keyword(s):  
Music Generation ◽  
Polyphonic Music

Algorithmic music generation by harmony recombination with genetic algorithm

2021 ◽  
pp. 1-13
Author(s):  
Omar Lopez-Rincon ◽  
Oleg Starostenko ◽  
Alejandro Lopez-Rincon
Keyword(s):  
Genetic Algorithm ◽  
New Music ◽  
Novel Approach ◽  
Time Patterns ◽  
Algorithmic Music ◽  
Long Time ◽  
Music Generation ◽  
Music Piece ◽  
Short Time ◽  
Algorithmic Music Composition

Algorithmic music composition has recently become an area of prestigious research in projects such as Google’s Magenta, Aiva, and Sony’s CSL Lab aiming to increase the composers’ tools for creativity. There are advances in systems for music feature extraction and generation of harmonies with short-time and long-time patterns of music style, genre, and motif. However, there are still challenges in the creation of poly-instrumental and polyphonic music, pieces become repetitive and sometimes these systems copy the original files. The main contribution of this paper is related to the improvement of generating new non-plagiary harmonic developments constructed from the symbolic abstraction from MIDI music non-labeled data with controlled selection of rhythmic features based on evolutionary techniques. Particularly, a novel approach for generating new music compositions by replacing existing harmony descriptors in a MIDI file with new harmonic features from another MIDI file selected by a genetic algorithm. This allows combining newly created harmony with a rhythm of another composition guaranteeing the adjustment of a new music piece to a distinctive genre with regularity and consistency. The performance of the proposed approach has been assessed using artificial intelligent computational tests, which assure goodness of the extracted features and shows its quality and competitiveness.

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