Diagrams allow to disambiguate between chord positions;
Using the previous position as context allows to suggest diagrams with:
More consistent texture;
More playable transitions.
D'Hooge et al. (2024), Guitar Chord
Diagram Suggestion for Western
Popular Music, SMC.
Assist Composition
Rhythm Guitar Tablature Continuation Through Picking Pattern Generation
Objective: Suggest possible continuation given a tablature
prompt and a chord
progression;
If any chord position is missing, it can be
suggested automatically
(D'Hooge et al. 2024).
House of the Rising Sun, The Animals.
House of the Rising Sun, The Animals.
Accompaniment parts in WPM are often repetitive;
Composers/Transcribers rely heavily on
copy-pasting;
Suggesting continuations can ease the
writing process and
propose variations;
Previous work lack chord progression
controls (except McVicar et
al. 2014).
Bacot et al. (2024), Enjeux du
logiciel de
tablatures dans l'acte de création en musiques actuelles : méthode d'entretien et
analyse
d'une pratique, JIM.
McVicar et al. (2014),
AutoRhythmGuitar:
Computer-aided composition
for Rhythm Guitar in the Tab Space, ICMC.
Chen et al. (2020), Automatic
Composition of
Guitar Tabs by
Transformers and Groove Modeling, ISMIR.
Loth et al. (2023), ProgGP: From
GuitarPro
Tablature Neural
Generation To Progressive Metal Production, CMMR.
Sarmento et al. (2023), GTR-CTRL:
Instrument
and Genre
Conditioning
for Guitar-Focused Music Generation with Transformers, EvoMUSART.
Assist Composition
Data Preparation of DadaGP
Identify rhythm guitar tracks (Régnier et al., 2021);
Extract 4-bar sequences with less than 75% rest time;
Convert to tokens.
Rule-Based Model
Transformer Model
Quantitative Evaluation
Edit Distance: Transformer outperforms rule-based model
significantly;
Texture Manhattan Distance the controls effectively drive the
transformer model to
change texture;
Out-of-Diagram notes:
Impossible for the rule-based model by design;
4% OoD notes ratio observed in the dataset;
At least 8% of OoD notes in what the transformer generates, even with a
dedicated loss function.
Online Survey for Subjective Evaluation
54 participants: 41 M, 3 F, 10 na; 46±16 years old.
Rate 5 prompts' continuations from:
Reference
Rule-based
Transformer
7-point Likert scales on:
Playability
Consistency
Interest
Usability
All continuations rated rather positively, with the reference preferred over both
models;
Preference for the rule-based model over the transformer despite
being
less controllable;
Prolonged use of the transformer model might be more appropriate
for
its evaluation.
Assist Composition
Bass Tablature Accompaniment Generation
Generated samples
    Olivier
Anoufa
Generate a bass guitar tablature conditioned on a rhythm guitar tablature.
A thematic analysis of the results suggest that:
The transformer model generates consistent musical content;
The bass lines feature idiomatic playing techniques;
The bass can sometimes be late/early when following the harmony.
The model is large and needs a few seconds to generate a bass track on GPU.
Anoufa et al. (2025), Conditional Generation of Bass Guitar Tablature
for
Guitar Accompaniment in Western Popular Music, AIMC.
Makris et al. (2022), Conditional Drums Generation Using Compound Word
Representations, EvoMUSART.
Assist Composition
Suggest Bends and Playing Techniques to Lead Guitarists
Suggest bends to add expressiveness and increase idiomaticity.
Nocturne Op.9 No.2, Frédéric Chopin (transposed to E
Major).
Feature-based Approach
Rhythm
Pitch
Gesture
Evaluate a note based on its neighbourhood
Four most important features:
Pitch of current note;
Pitch distance to next note;
Pitch distance to previous note;
Current note's duration.
Nocturne Op.9 No.2, Frédéric Chopin (transposed to E Major), arranged by K I L L
J E S T E R
Possible to extend to other techniques. Statistics used by Bontempi et al. (2024) to add
expressiveness to melodies.
Bontempi et al. (2024), From MIDI to Rich Tablatures: an Automatic
Generative System incorporating Lead Guitarists' Fingering and Stylistic choices,
SMC.
Assist Learning and Practice
There are a lot of online resources available to guitarists.
There are a lot of online resources available to guitarists:
Tab Websites
UltimateGuitar;
Songsterr;
911tabs...
There are a lot of online resources available to guitarists:
Tab Websites
UltimateGuitar;
Songsterr;
911tabs...
Online Courses
YouTube channels
justinGuitar
Synner
Fender Play...
There are a lot of online resources available to guitarists:
Tab Websites
UltimateGuitar;
Songsterr;
911tabs...
Online Courses
YouTube channels
justinGuitar
Synner
Fender Play...
Apps
Yousician
Simply Guitar
Rocksmith+
There are a lot of online resources available to guitarists:
Tab Websites
Online Courses
Apps
Existing research focused on:
Gathering resources for learning a song or
chords;
Assist beginners in learning new songs;
Analyse the difficulty of songs based on
their
chords.
The learner's level is rarely modelled, except in Müllerschön et al. (2025).
Barthet et al. (2011), Music
Recommendation for
Music Learning: Hottabs, a Multimedia Guitar Tutor, WOMRAD.
Xambó et al. (2018), Jam with
Jamendo:
Querying
a Large Music Collection by Chords from a Learner's Perspective, Audio
Mostly.
Ariga et al. (2017), Strummer: An
Interactive Guitar Chord Practice System, ICME.
Vélez Vasquéz et al. (2023),
Quantifying the Ease of Playing Song Chords on the Guitar, ISMIR.
Müllerschön et al. (2025), Playability
Prediction in Digital
Guitar Learning using Interpretable Student and Song Representations, ISMIR.
Assist Learning and Practice
Difficulty-informed Song Recommendations
New dataset of over 200 difficulty-rated WPM rhythm guitar
songs.
Yohann Abbou
Mathieu Giraud
Gilles Guillemain
Aurélien Jeanneau
Zakaria Hassein-Bey
Assist Learning and Practice
Interpretable Tablature Difficulty Analysis
New dataset of approx. 1000 difficulty-rated tablatures.
Songs to practice weekly for rhythm, lead or bass guitar. Difficulty ratings are
numerical and categorical:
1-3: Beginner;
4-5: Intermediate;
6-7: Advanced;
8-9: Master;
10: Expert.
Vsevolod Eremenko
Pedro Ramoneda
Radio Song, Superbus. Rhythm Guitar - B
Beggin', Måneskin. Bass Guitar - I
Ijime, Dame, Zettai, BABYMETAL. Lead Guitar -
M
Feature Engineering approach, based on the
curricula
of music
diplomas and past research on
piano and guitar difficulty.
Feature Groups:
Speed;
Stamina;
Structure/Repetition;
Technique;
Rhythm;
Pitch/Fretboard Position.
Lead Guitar
Bass Guitar
Chiu et al. (2012), A Study on Difficulty Level Recognition of Piano
Sheet Music, Int. Symposium on Multimedia.
Vélez Vásquez et al. (2023), Quantifying the Ease of Playing Song
Chords on the Guitar, ISMIR.