Guitar Fingering For Music Performance

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GUITAR FINGERING FOR MUSIC PERFORMANCE
Vincenzo Lombardo
Daniele Radicioni
CIRMA,
Centro di Scienza Cognitiva
Centro di Scienza Cognitiva,
Universit` a e Politecnico di Torino
Dipartimento di Informatica
Via Po, 14 - 10123 Torino, Italy
Universit` a di Torino
Corso Svizzera, 185 - 10149 Torino, Italy
frets
0
I
II
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VIII
IX
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XI
XII
ABSTRACT
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This paper presents a computational model of fingering
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for string instruments, based on a graph search approach.
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The implemented fingering model, which accounts for the
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bio-mechanical constraints of the performer’s hand, is in-
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terfaced with a physical model of the classical guitar, which
Figure 1. Outline of the notes (indicated as MIDI num-
exploits the fingering to compute some sound synthesis
bers) on a guitar fingerboard, showing that the same tone
parameters. The output of the system is validated against
can be found on up to 4 different positions, i.e., the case of
the performance of a human expert.
E treble (MIDI number 64), that lies at
1,0 ,
2,5 ,
(the figure displays only the first XII
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1. INTRODUCTION
frets). The fret 0 indicates notes produced by plucking the
string without pressing any fret.
Fingering is a cognitive process that maps each note on
a music score to a fingered position on some instrument.
Fingering involves several competences: i) musical anal-
that are implied in left hand movements of guitarists. In
ysis (including both structural and aesthetical issues), for
the modeling area, Parncutt et al. [5] (lately updated by
the interpretation of the notes in input, ii) physical con-
Jacobs [4]), on piano playing, and Sayegh [8] on the gui-
straints, posed by the instrument where the notes have to
tar, have implemented the principle of penalizing difficul-
be played, iii) bio-mechanical constraints, which charac-
ties. Cabral et al. model [1] also includes frequency in the
terize the possible figures of the hand. However, despite
repertoire.
the salience of fingering in music performance, scores of-
In previous papers we have addressed two separate ca-
ten lack of fingering indications, considered unnecessary
ses of translating the notes in the score into the actual ex-
(being common knowledge within a certain musical prac-
ecutor’s gestures, namely the case of melodies of individ-
tice) or an execution choice. In the present paper we pro-
ual notes [6], and the case of isolated chords [7]. In this
pose a general model for providing pieces with finger-
paper we improve the fingering model in accounting for
ing, and we focus on physical and bio-mechanical con-
both cases, so that it assigns fingerings to melodies that
straints, leaving the contribution of musical analysis to a
also include chords and polyphonic passages (e.g., when
later work.
a note is held, and new notes are to be played). The over-
The fingering problem consists in determining for each
all methodology transports Parncutt ergonomic approach
note in the score, a position
on the fin-
<string,fret>
[5] from keyboard to guitar, and shares the graph search
gerboard and a finger of the left hand that presses it. The
framework with [8]. The novelties of our approach lie
notion of position provides a unique identifier for the cor-
in the facts that we tackle melodies formed by individual
respondence between the note and the fingerboard. A fin-
notes and chords, by applying the same physical and bio-
gered position is the triple
, com-
<string,fret,finger>
mechanical sources of difficulty to both succession and
bining a position with one of the four available fingers.
simultaneity of positions, and that we provide an experi-
Provided that guitarists do use four fingers of the left hand
mental validation of the approach.
(from the index to the little finger), n notes generate up to
4 different fingerings. Since the same note can be found
on up to 4 positions (Figure 1), this number might grow
2. FINGERING AS GRAPH SEARCH PROBLEM
up to 16 .
Works from several scientific areas approached finger-
Given a music score, we build a graph that represents all
ing for its contributions to music performance [9]. Hei-
the possible fingered positions sequences. For each note
jink & Meulenbroek [3] have carried out ergonomic and
from left to right in the score we generate all the possi-
motor behavioral studies based on the complexity factors
ble fingered positions for that note (Figure 2). This con-

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