Modelling of natural sounds by time–frequency and wavelet  representations

In this paper, we focused on the identification of the perceptual properties of impacted materials to provide an intuitive control of an impact sound synthesizer. To investigate such properties, impact sounds from everyday life objects, made of different materials (wood, metal and glass), were recorded and analyzed. These sounds were synthesized using an analysis-synthesis technique and tuned to the same chroma. Sound continua were created to simulate progressive transitions between materials. Sounds from these continua were then used in a categorization experiment to determine sound categories representative of each material (called typical sounds). We also examined changes in electrical brain activity (using event related potentials (ERPs) method) associated with the categorization of these typical sounds. Moreover, acoustic analysis was conducted to investigate the relevance of acoustic descriptors known to be relevant for both timbre perception and material identification. Both acoustic and electrophysiological data confirmed the importance of damping and highlighted the relevance of spectral content for material perception. Based on these findings, controls for damping and spectral shaping were tested in synthesis applications. A global control strategy, with a threelayer architecture, was proposed for the synthesizer allowing the user to intuitively navigate in a "material space" and defining impact sounds directly from the material label. A formal perceptual evaluation was finally conducted to validate the proposed control strategy.

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“…( [30] (see also [31], [32]). These latter methods provide an accurate estimation and can be used to conduct spectral analysis.…”

Section: B Stimulimentioning

confidence: 98%

Controlling the Perceived Material in an Impact Sound Synthesizer

Aramaki

Besson

Kronland‐Martinet

et al. 2011

IEEE Trans. Audio Speech Lang. Process.

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“…In the 1960s when computer music was at its very beginning, the famous scientist John Pierce made the following enthusiastic statement about sounds made from computers: "wonderful things would come out of that box if only we knew how to evoke [emphasis added] them" (Pierce 1965, p. 150). In spite of the many synthesis algorithms that have been developed so far and that provide perfect resynthesis of sounds, meaning that no difference is perceived between the original and the synthesized sound (Kronland-Martinet et al 1997;Cook and Scavone 1999;Bensa et al 2003, Bilbao andWebb 2013), the issue of control is still a great challenge that prevents many potential users from considering sound synthesis in their applications. This issue has always interested composers and musicians, and a large number of interfaces and control strategies for digital sound synthesis have already been proposed in the musical domain (Moog 1987;Cook 2001;Gobin et al 2003, Miranda andWanderley 2006).…”

Section: Towards Intuitive Controls Of Soundsmentioning

confidence: 99%

Timbre from Sound Synthesis and High-Level Control Perspectives

Ystad

Aramaki

Kronland‐Martinet

2019

Timbre: Acoustics, Perception, and Cognition

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Exploring the many surprising facets of timbre through sound manipulations has been a common practice among composers and instrument makers of all times. The digital era radically changed the approach to sounds thanks to the unlimited possibilities offered by computers that made it possible to investigate sounds without physical constraints. In this chapter, we describe investigations on timbre based on the analysis-by-synthesis approach that consists of using digital synthesis algorithms to reproduce sounds and further modify the parameters of the algorithms to investigate their perceptual relevance. In the first part of the chapter, timbre is investigated in a musical context. An examination of the sound quality of different wood species for xylophone making is first presented. Then the influence of physical control on instrumental timbre is described in the case of clarinet and cello performances. In the second part of the chapter, environmental sounds have been investigated in order to identify so-called invariant sound structures that can be considered as the backbone, or the bare minimum, of the information contained in a sound that enables the listener to recognize its source both in terms of structure (e.g. size, material) and action (e.g. hitting, scraping). Such invariants are generally composed of combinations of audio descriptors such as decay, attack, spectral density and pitch. Various investigations on perceived sound properties responsible for the evocations of sound sources are here identified and described through both applied and fundamental studies.

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“…To estimate the damping factor associated with each modal component of the signal, we used a signal processing technique based on the theory of analytic signals. 24,25 The analytic signal representation provides an easy way of extracting both the instantaneous frequency and the damping of each modal component, through band-pass filtering. To isolate each component in frequency, we used a truncated Gaussian window, the frequency bandwidth of which was chosen so as to minimize smoothing effects over the attack duration and to avoid overlapping two successive frequency components.…”

Section: B Estimation Of Parametersmentioning

confidence: 99%

The simulation of piano string vibration: From physical models to finite difference schemes and digital waveguides

Bensa

Bilbao

Kronland‐Martinet

et al. 2003

The Journal of the Acoustical Society of America

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A model of transverse piano string vibration, second order in time, which models frequency-dependent loss and dispersion effects is presented here. This model has many desirable properties, in particular that it can be written as a well-posed initial-boundary value problem (permitting stable finite difference schemes) and that it may be directly related to a digital waveguide model, a digital filter-based algorithm which can be used for musical sound synthesis. Techniques for the extraction of model parameters from experimental data over the full range of the grand piano are discussed, as is the link between the model parameters and the filter responses in a digital waveguide. Simulations are performed. Finally, the waveguide model is extended to the case of several coupled strings.

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Modelling of natural sounds by time–frequency and wavelet representations

Cited by 11 publications

References 28 publications

Controlling the Perceived Material in an Impact Sound Synthesizer

Controlling the Perceived Material in an Impact Sound Synthesizer

Timbre from Sound Synthesis and High-Level Control Perspectives

The simulation of piano string vibration: From physical models to finite difference schemes and digital waveguides

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