Satoru Fukayama
Biographic Data
| ID | 2787889 |
|---|---|
| NAME | Satoru Fukayama |
| GIVEN NAMES | Satoru |
| FAMILY NAME | Fukayama |
| SIGNATURE | FUKAYAMA S |
| AFFILIATIONS | National Institute of Advanced Industrial Science and Technology |
| ORCID | 0000-0001-6506-2796 |
| VERIFIED | Yes |
| TOTAL WORKS | 3 |
| TOTAL CITATIONS | 2 |
| WORKS AS AUTHOR | 3 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2013 |
| LATEST PUBLICATION YEAR | 2021 |
| H-INDEX | 1 |
Automatic melody harmonization with triad chords
The task of automatic melody harmonization aims to build a model that generates a chord sequence as the harmonic accompaniment of a given multiple-bar melody sequence. In this paper, we present a comparative study evaluating the performance of canonical approaches to this task, including template matching, hidden Markov model, genetic algorithm and deep learning. The evaluation is conducted on a dataset of 9226 melody/chord pairs, considering 48 …
The CrossSong Puzzle
There is considerable interest in music-based games and apps. However, in existing games, music generally serves as an accompaniment or as a reward for progress. We set out to design a game where paying attention to the music would be essential to making deductions and solving the puzzle. The result is the CrossSong Puzzle, a novel type of music-based logic puzzle that integrates musical and logical reasoning. The game presents a player with a gr…
Melody Harmonization With Interpolated Probabilistic Models
Most melody harmonization systems use the generative hidden Markov model (HMM), which model the relation between the hidden chords and the observed melody. Relations to other variables, such as the tonality or the metric structure, are handled by training multiple HMMs or are ignored. In this paper, we propose a discriminative means of combining multiple probabilistic models of various musical variables by means of model interpolation. We evaluat…
Melody Harmonization With Interpolated Probabilistic Models
Most melody harmonization systems use the generative hidden Markov model (HMM), which model the relation between the hidden chords and the observed melody. Relations to other variables, such as the tonality or the metric structure, are handled by training multiple HMMs or are ignored. In this paper, we propose a discriminative means of combining multiple probabilistic models of various musical variables by means of model interpolation. We evaluat…
Melody Harmonization With Interpolated Probabilistic Models
Most melody harmonization systems use the generative hidden Markov model (HMM), which model the relation between the hidden chords and the observed melody. Relations to other variables, such as the tonality or the metric structure, are handled by training multiple HMMs or are ignored. In this paper, we propose a discriminative means of combining multiple probabilistic models of various musical variables by means of model interpolation. We evaluat…
The CrossSong Puzzle
There is considerable interest in music-based games and apps. However, in existing games, music generally serves as an accompaniment or as a reward for progress. We set out to design a game where paying attention to the music would be essential to making deductions and solving the puzzle. The result is the CrossSong Puzzle, a novel type of music-based logic puzzle that integrates musical and logical reasoning. The game presents a player with a gr…
Automatic melody harmonization with triad chords
The task of automatic melody harmonization aims to build a model that generates a chord sequence as the harmonic accompaniment of a given multiple-bar melody sequence. In this paper, we present a comparative study evaluating the performance of canonical approaches to this task, including template matching, hidden Markov model, genetic algorithm and deep learning. The evaluation is conducted on a dataset of 9226 melody/chord pairs, considering 48 …
Computer Science (3 works) · Music and Audio Processing (3 works) · Music Technology and Sound Studies (3 works) · Artificial Intelligence (2 works) · Harmonization (2 works) · Hidden Markov model (2 works) · Musical (2 works) · Neuroscience and Music Perception (2 works) · Speech recognition (2 works) · Art (1 work)