Extraction and analysis of body-induced partials of guitar tones

Abstract

Guitar plucked sounds arise from a rapid input of energy applied to the string coupled to the instrument body at the bridge. For the radiated pressure, this results in quasi-harmonic contributions, reflecting the string modes coupled to the body, as well as some transient and quickly decaying components reflecting the excitation of the body modes of the instrument. In order to evaluate the relevance of this transient body sound, a high resolution analysis-synthesis method is described for the extraction of the body-mode contribution from the radiated pressure measured in the near field of the guitar top plate. This analysis scheme is first tested on synthesized signals. Some body-sound emergence indicators are then proposed and computed over a pool of instruments. The influence of the conditions of excitation on the body-sound emergence is investigated, and the instruments categorized according to these objective descriptors. Results show a larger range of body-sound emergence with variations of the plucking position in hand-made guitars compared to industrial instruments. This suggests that these particular hand-made instruments are more sensitive to variations in the control from the player and hence allow a wider range of timbres with respect to the transient coloration of the body modes.

Acoustics of the banjo: measurements and sound synthesis

“…A similar mechanism has been suggested for distinguishing different violins by their transient sound [40]. Fréour et al [31] have studied the audibility of comparable body sounds in guitar notes, with the conclusion that the effect is confined to frequencies below about 1 kHz and is strongest for the low modes below 300 Hz, in keeping with the impression given by Figure 2b. For the banjo, Figures 2a and 12 suggest that the effect may extend over a wider frequency range, but this has yet to be formally tested.…”

“…For a more fine-grained view, the chromatic scales on the top strings of the banjo and guitar can be analysed in a different way. The detailed test procedure has been described in earlier papers [15,30], and a related test methodology has been used by Fréour et al [31]. Time-frequency analysis can be used to determine the best-fitted frequency and decay rate of every spectral peak satisfying a set of criteria to ensure data quality.…”

Numerical continuation of a physical model of brass instruments: Application to trumpet comparisons

“…Several studies attempt to provide answers to that complex problem with more or less success [19]. Another complementary approach consists of extracting objective descriptors from measurements, with the aim to categorize and highlight differences between instruments on the basis of more advanced or meaningful indicators [20][21][22], the underlying assumption being that these indicators may then be easier to correlate to perceptual data. Some studies have followed this strategy, particularly in string instruments.…”

The High-Resolution Wavevector Analysis for the characterization of the dynamic response of composite plates

“…In some applications of the ESTER criterion [46,12,44], a threshold parameter is added: the signal order is chosen as the largest value r for which the criterion reaches a local maximum larger than a fraction of the global maximum. In the present work, this strategy was not used.…”

“…Another example is the ERA [36] (Eigenvalue Realisation Algorithm), which is devoted to the identification of the modal parameters of a measured system. A wide range of applications of the ESPRIT algorithm can be found in array processing and radar applications [37,38], audio processing [39,40], characterization of structures through modal analysis [12,13,23], musical acoustics applications [41,42,43,44] and high-resolution spectral analysis [45]. To be fully efficient, the ESPRIT algorithm must be combined with a criterion dedicated to the the estimation of the signal order, such as the ESTER criterion [46] (ESTimation of ERror)…”