An HMM-Based Approach for Cross-Harmonization of Jazz Standards
This paper presents a methodology for generating cross-harmonizations of jazz standards, i.e., for harmonizing the melody of a jazz standard (Song A) with the harmonic context of another (Song B). Specifically, the melody of Song A, along with the chords that start and end its sections (chord constr...
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-01-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/13/3/1338 |
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| author | Maximos Kaliakatsos-Papakostas Konstantinos Velenis Leandros Pasias Chrisoula Alexandraki Emilios Cambouropoulos |
| author_facet | Maximos Kaliakatsos-Papakostas Konstantinos Velenis Leandros Pasias Chrisoula Alexandraki Emilios Cambouropoulos |
| author_sort | Maximos Kaliakatsos-Papakostas |
| collection | DOAJ |
| description | This paper presents a methodology for generating cross-harmonizations of jazz standards, i.e., for harmonizing the melody of a jazz standard (Song A) with the harmonic context of another (Song B). Specifically, the melody of Song A, along with the chords that start and end its sections (chord constraints), are used as a basis for generating new harmonizations with chords and chord transitions taken from Song B. This task involves potential incompatibilities between the components drawn from the two songs that take part in the cross-harmonization. In order to tackle such incompatibilities, two methods are introduced that are integrated in the Hidden Markov Model and the Viterbi algorithm. First, a rudimentary approach to chord grouping is presented that allows interchangeable utilization of chords belonging to the same group, depending on melody compatibility. Then, a “supporting” harmonic space of chords and probabilities is employed, which is learned from the entire dataset of the available jazz standards; this space provides local solutions when there are insurmountable conflicts between the melody and constraints of Song A and the harmonic context of Song B. Statistical and expert evaluation allow an analysis of the methodology, providing valuable insight about future steps. |
| first_indexed | 2024-03-11T09:53:04Z |
| format | Article |
| id | doaj.art-7eb0e0b4998a49a78468154bd78d3eee |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-11T09:53:04Z |
| publishDate | 2023-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-7eb0e0b4998a49a78468154bd78d3eee2023-11-16T16:04:00ZengMDPI AGApplied Sciences2076-34172023-01-01133133810.3390/app13031338An HMM-Based Approach for Cross-Harmonization of Jazz StandardsMaximos Kaliakatsos-Papakostas0Konstantinos Velenis1Leandros Pasias2Chrisoula Alexandraki3Emilios Cambouropoulos4School of Music Studies, Aristotle University of Thessaloniki, 541 24 Thessaloniki, GreeceSchool of Music Studies, Aristotle University of Thessaloniki, 541 24 Thessaloniki, GreeceSchool of Music Studies, Aristotle University of Thessaloniki, 541 24 Thessaloniki, GreeceDepartment of Music Technology and Acoustics, Hellenic Mediterranean University, 741 33 Rethymno, GreeceSchool of Music Studies, Aristotle University of Thessaloniki, 541 24 Thessaloniki, GreeceThis paper presents a methodology for generating cross-harmonizations of jazz standards, i.e., for harmonizing the melody of a jazz standard (Song A) with the harmonic context of another (Song B). Specifically, the melody of Song A, along with the chords that start and end its sections (chord constraints), are used as a basis for generating new harmonizations with chords and chord transitions taken from Song B. This task involves potential incompatibilities between the components drawn from the two songs that take part in the cross-harmonization. In order to tackle such incompatibilities, two methods are introduced that are integrated in the Hidden Markov Model and the Viterbi algorithm. First, a rudimentary approach to chord grouping is presented that allows interchangeable utilization of chords belonging to the same group, depending on melody compatibility. Then, a “supporting” harmonic space of chords and probabilities is employed, which is learned from the entire dataset of the available jazz standards; this space provides local solutions when there are insurmountable conflicts between the melody and constraints of Song A and the harmonic context of Song B. Statistical and expert evaluation allow an analysis of the methodology, providing valuable insight about future steps.https://www.mdpi.com/2076-3417/13/3/1338Hidden Markov Modelmelodic harmonizationjazz standardscomputational creativity |
| spellingShingle | Maximos Kaliakatsos-Papakostas Konstantinos Velenis Leandros Pasias Chrisoula Alexandraki Emilios Cambouropoulos An HMM-Based Approach for Cross-Harmonization of Jazz Standards Applied Sciences Hidden Markov Model melodic harmonization jazz standards computational creativity |
| title | An HMM-Based Approach for Cross-Harmonization of Jazz Standards |
| title_full | An HMM-Based Approach for Cross-Harmonization of Jazz Standards |
| title_fullStr | An HMM-Based Approach for Cross-Harmonization of Jazz Standards |
| title_full_unstemmed | An HMM-Based Approach for Cross-Harmonization of Jazz Standards |
| title_short | An HMM-Based Approach for Cross-Harmonization of Jazz Standards |
| title_sort | hmm based approach for cross harmonization of jazz standards |
| topic | Hidden Markov Model melodic harmonization jazz standards computational creativity |
| url | https://www.mdpi.com/2076-3417/13/3/1338 |
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