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CHORD JAZZIFICATION LEARNING JAZZ INTERPRETATIONS OF CHORD SYMBOLS Tsung-Ping Chen 1 , Satoru Fukayama 2 , Masataka Goto 2 , and Li Su 1 1 Music and Culture Technology Lab, Institute of Information Science, Academia Sinica, Taiwan 2 National Institute of Advanced Industrial Science and Technology (AIST), Japan INTRODUCTION Chord symbols provide basic guides to musical harmony There are various ways to interpret chord symbols RESEARCH AIM Generating jazz voicings from chord symbols (triads only) METHODS Compiling chord voicings in pop-jazz sheet music Two-stage jazzification (coloring and voicing) using supervised learning THE NEW DATASET 50 pop-jazz piano solos 6700 chords (796 phrases) Sheet music Voicing Roman numeral analysis Coloring THE ANNOTATIONS TWO-STAGE CHORD JAZZIFICATION COLORING Selecting a set of pitch classes (p i ) and a bass (b i ) for the rendering of each chord symbol VOICING Selecting in which octaves each pitch class is actually played on the keyboard (v i ) c c COLORING MODEL duration of chroma representation of the ith chord Input Output softmax-activated bass vector sigmoid-activated pitch class vector Computation VOICING MODEL pitch class vector bass vector Input Output Computation voicing vector duration of EVALUATION ON THE PROPOSED DATASET p i b i v i PITCH CLASSES Multi-label classification Accuracy BASS Multi-class Classification Accuracy VOICING Multi-label classification Accuracy C C SEQUENCE MODELLING COLORING VOICING BASS PITCH CLASSES BI-DIRECTIONAL LSTM 81.87 76.52 63.64 MULTIHEAD SELF-ATTENTION 80.78 77.02 64.86 END-TO-END - - 37.87 Result CHORD JAZZIFICATION TEST ON THE JAZZ AUDIO-ALIGNED HARMONY (JAAH) DATASET minor 7th 7b9 chords 1st inversion JAZZIFICATION EXAMPLES F Edim A Dm G Cm F Bb Bbm Eb Am D Abm Db Gm C F F Cm F Cm F Bb Db Gb B CONCLUSION By formulating the chord jazzification as two-stage classification problems, we showed that the proposed framework is capable of generating jazz voicings directly from chord symbols. The chord jazzification can be applied to scenarios such as music performing and composing. THANK YOU Do you have any questions? Tsung-Ping Chen [email protected] CREDITS: This presentation template was created by Slidesgo , including icons by Flaticon , and infographics & images by Freepik GitHub Lab

CHORD JAZZIFICATION...Generating jazz voicings from chord symbols ( triads only ) METHODS Compiling chord voicings in pop -jazz sheet music Two -stage jazzification ( coloring and

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Page 1: CHORD JAZZIFICATION...Generating jazz voicings from chord symbols ( triads only ) METHODS Compiling chord voicings in pop -jazz sheet music Two -stage jazzification ( coloring and

CHORD JAZZIFICATIONLEARNING JAZZ INTERPRETATIONS OF CHORD SYMBOLS

Tsung-Ping Chen1, Satoru Fukayama2, Masataka Goto2, and Li Su1

1Music and Culture Technology Lab, Institute of Information Science, Academia Sinica, Taiwan2National Institute of Advanced Industrial Science and Technology (AIST), Japan

INTRODUCTION

◆ Chord symbols provide basic guides to musical harmony

◆ There are various ways to interpret chord symbols

RESEARCH AIM

◆ Generating jazz voicings from chord symbols (triads only)

METHODS

◆ Compiling chord voicings in pop-jazz sheet music

◆ Two-stage jazzification (coloring and voicing) using supervised learning

THE NEW DATASET

◆ 50 pop-jazz piano solos

◆ 6700 chords (796 phrases)

Sheet music

Voicing

Roman numeral analysis

Coloring

THE ANNOTATIONS

TWO-STAGE CHORD JAZZIFICATION

COLORING

Selecting a set of pitchclasses (pi) and a bass (bi)for the rendering of eachchord symbol

VOICING

Selecting in which octaveseach pitch class is actuallyplayed on the keyboard (vi)

c c

COLORING MODEL

duration of

chroma representation of the ith chord

Input

Output

softmax-activated bass vector

sigmoid-activated pitch class vector

Computation

VOICING MODEL

pitch class vector

bass vector

Input

Output

Computation

voicing vector

duration of

EVALUATIONON THE PROPOSED DATASET

pi bi vi

PITCH

CLASSES

Multi-labelclassification

Accuracy

BASS

Multi-classClassification

Accuracy

VOICING

Multi-labelclassification

Accuracy

C C

SEQUENCEMODELLING

COLORINGVOICING

BASS PITCH CLASSES

BI-DIRECTIONALLSTM

81.87 76.52 63.64

MULTIHEADSELF-ATTENTION

80.78 77.02 64.86

END-TO-END - - 37.87

Result

CHORD JAZZIFICATION TESTON THE JAZZ AUDIO-ALIGNED HARMONY (JAAH) DATASET

minor 7th

7b9 chords

1st inversion

JAZZIFICATION EXAMPLES

F Edim A Dm G Cm F Bb Bbm Eb Am D Abm Db Gm C F F

Cm F Cm F Bb Db Gb B

CONCLUSION

◆ By formulating the chord jazzification as two-stage classification problems,we showed that the proposed framework is capable of generating jazzvoicings directly from chord symbols.

◆ The chord jazzification can be applied to scenarios such as music performingand composing.

CREDITS: This presentation template was created by Slidesgo, including icons by Flaticon, and infographics & images by Freepik

THANK

YOUDo you have any questions?

Tsung-Ping [email protected]

CREDITS: This presentation template was created by Slidesgo, including icons by Flaticon, and infographics & images by Freepik

GitHub Lab