Paper Archive

This paper presents a novel method of analysing drum sounds, demonstrating that this can form the basis of a highly realistic synthesis technique for real-time use. The synthesis method can be viewed as an extension of IFFT synthesis; here we exploit the fact that audio signals can be recovered from solely the real component of their discrete Fourier transform (RDFT). All characteristics of an entire drum sample can therefore be conveniently encoded in a single, real-valued, frequency domain signal. These signals are interpreted, incorporating the physics of the instrument, and modelled to investigate how the perceptual features are encoded. The model was able to synthesize drum sound components in such detail that they could not be distinguished in an ABX test. This method may therefore be capable of outperforming existing synthesis techniques, in terms of realism. Sound examples available here.

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This paper describes a computationally efficient synthesis model for snare drum sounds. Its parameters can be modulated at audio rate while being played. The input to the model is an acoustic excitation signal which carries spectral information to color the output sound. This makes it suitable for acoustic interfaces – devices which provide excitation signal and control data simultaneously. The presented synthesis model builds up on work done by Miller Puckette and processes audio input from a piezoelectric microphone into a nonlinear reverberator. This paper details a strikingly simple but novel approach on how to make use of the momentary DC offset generated by piezoelectric microphones when pressed to simulate the changes in drumhead tension. This technique is especially of interest for interfaces without pressure sensing capabilities. In the design process we pursued an experimental approach rather than a purely mathematical. Implementations of the synthesis model are provided for Pure Data and FAUST as open source.

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Recent advancements in generative audio synthesis have allowed for the development of creative tools for generation and manipulation of audio. In this paper, a strategy is proposed for the synthesis of drum sounds using generative adversarial networks (GANs). The system is based on a conditional Wasserstein GAN, which learns the underlying probability distribution of a dataset compiled of labeled drum sounds. Labels are used to condition the system on an integer value that can be used to generate audio with the desired characteristics. Synthesis is controlled by an input latent vector that enables continuous exploration and interpolation of generated waveforms. Additionally we experiment with a training method that progressively learns to generate audio at different temporal resolutions. We present our results and discuss the benefits of generating audio with GANs along with sound examples and demonstrations.

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This paper introduces complementary n-gon waves and the shuffled samples noise effect. N-gon waves retain angles of the regular polygons and star polygons of which they are derived from in the waveform itself. N-gon waves are researched by the author since 2000 and were introduced to the public at ICMC|SMC in 2014. Complementary n-gon waves consist of an n-gon wave and a complementary angular wave. The complementary angular wave introduced in this paper complements an n-gon wave so that the two waveforms can be used to reconstruct the polygon of which the waveforms were derived from. If it is derived from a star polygon, it is not an n-gon wave and has its own characteristics. Investigations into how geometry, audio, visual and perception are related led to experiments with complementary n-gon waves and a shuffle algorithm. It is possible to reconstruct a digitised geometric shape from its shuffled samples and visualise the geometric shape with shuffled samples noise signals on a digital display device or also, within some limitations, on an oscilloscope in X-Y mode. This paper focuses on the description of discrete complementary n-gon waves and how a Fisher-Yates shuffle algorithm was applied to these waveforms and used to create the shuffled samples noise effect. In addition, some of the timbral and spatial characteristics of complementary n-gon waves and shuffled samples noise are outlined and audiovisual applications of these waveforms briefly discussed.

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Matching pursuit (MP) algorithms are widely used greedy methods to find K-sparse signal approximations in redundant dictionaries. We present an acceleration technique and an implementation of the matching pursuit algorithm acting on a multi-Gabor dictionary, i.e., a concatenation of several Gabor-type time-frequency dictionaries, consisting of translations and modulations of possibly different windows, time- and frequency-shift parameters. The proposed acceleration is based on pre-computing and thresholding inner products between atoms and on updating the residual directly in the coefficient domain, i.e., without the round-trip to the signal domain. Previously, coefficient-domain residual updates have been dismissed as having prohibitive memory requirements. By introducing an approximate update step, we can overcome this restriction and greatly improve the performance of matching pursuit at a modest cost in terms of approximation quality per selected atom. An implementation in C with Matlab and GNU Octave interfaces is available, outperforming the standard Matching Pursuit Toolkit (MPTK) by a factor of 3.5 to 70 in the tested conditions. Additionally, we provide experimental results illustrating the convergence of the implementation.

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Physical accuracy of virtual acoustics receives increasing attention due to renewed interest in virtual and augmented reality applications. So far, the modeling of vibrating objects as point sources is a common simplification which neglects effects caused by their spatial extent. In this contribution, we propose a technique for the interconnection of a distributed source to a room model, based on a modal representation of source and room. In particular, we derive a connection matrix that describes the coupling between the modes of the source and the room modes in an analytical form. Therefore, we consider the example of a string that is oscillating in a room. Both, room and string rely on well established physical descriptions that are modeled in terms of transfer functions. The derived connection of string and room defines the coupling between the characteristic string and room modes. The proposed structure is analyzed by numerical evaluations and sound examples on the supplementary website.

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Slide-string instruments allow continuous control of pitch by articulation with a slide object whose position of contact with the string is time-varying. This paper presents a method for simulation of such articulation. Taking into account sensing and musical practice considerations, an appropriate physical model configuration is determined, which is then formulated in numerical form using a finite difference approach. The model simulates the attachment and detachment phases of slide articulation which generally involve rattling, while finger damping is modelled in a more phenomenological manner as a regionally induced time-varying damping. A stability bound for the numerical model is provided via energy analysis, which also reveals the driving power contributions of the separate articulatory sources. The approach is exemplified with simulations of slide articulatory gestures that involve glissando, vibrato and finger damping.

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This paper proposes a new macroscopic physical model of ferromagnetic coils used in audio circuits. To account for realistic saturation and hysteretic phenomena, this model combines statistical physics results, measurement-driven refinements and portHamiltonian formulations that guarantee passivity, thermodynamic consistency and composability according to both electric and thermal ports. As an illustration, the model is used to simulate a passive high-pass filter. Different types of audio inputs are considered and simulations are compared to measurements.

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Feedback delay networks (FDNs) are recursive filters, which are widely used for artificial reverberation and decorrelation. While there exists a vast literature on a wide variety of reverb topologies, this work aims to provide a unifying framework to design and analyze delay-based reverberators. To this end, we present the Feedback Delay Network Toolbox (FDNTB), a collection of the MATLAB functions and example scripts. The FDNTB includes various representations of FDNs and corresponding translation functions. Further, it provides a selection of special feedback matrices, topologies, and attenuation filters. In particular, more advanced algorithms such as modal decomposition, time-varying matrices, and filter feedback matrices are readily accessible. Furthermore, our toolbox contains several additional FDN designs. Providing MATLAB code under a GNU-GPL 3.0 license and including illustrative examples, we aim to foster research and education in the field of audio processing.

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Artificial reverberation is an audio effect used to simulate the acoustics of a space while controlling its aesthetics, particularly on sounds recorded in a dry studio environment. Delay-based methods are a family of artificial reverberators using recirculating delay lines to create this effect. The feedback delay network is a popular delay-based reverberator providing a comprehensive framework for parametric reverberation by formalizing the recirculation of a set of interconnected delay lines. However, one known limitation of this algorithm is the initial slow build-up of echoes, which can sound unrealistic, and overcoming this problem often requires adding more delay lines to the network. In this paper, we study the effect of adding velvet-noise filters, which have random sparse coefficients, at the input and output branches of the reverberator. The goal is to increase the echo density while minimizing the spectral coloration. We compare different variations of velvet-noise filtering and show their benefits. We demonstrate that with velvet noise, the echo density of a conventional feedback delay network can be exceeded using half the number of delay lines and saving over 50% of computing operations in a practical configuration using low-order attenuation filters.

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