Download Dark Velvet Noise This paper proposes dark velvet noise (DVN) as an extension of the original velvet noise with a lowpass spectrum. The lowpass spectrum is achieved by allowing each pulse in the sparse sequence to have a randomized pulse width. The cutoff frequency is controlled by the density of the sequence. The modulated pulse-width can be implemented efficiently utilizing a discrete set of recursive running-sum filters, one for each unique pulse width. DVN may be used in reverberation algorithms. Typical room reverberation has a frequency-dependent decay, where the high frequencies decay faster than the low ones. A similar effect is achieved by lowering the density and increasing the pulse-width of DVN in time, thereby making the DVN suitable for artificial reverberation.
Download Streamable Neural Audio Synthesis with Non-Causal Convolutions Deep learning models are mostly used in an offline inference fashion. However, this strongly limits the use of these models inside audio generation setups, as most creative workflows are based on real-time digital signal processing. Although approaches based on recurrent networks can be naturally adapted to this buffer-based computation, the use of convolutions still poses some serious challenges. To tackle this issue, the use of causal streaming convolutions have been proposed. However, this requires specific complexified training and can impact the resulting audio quality. In this paper, we introduce a new method allowing to produce non-causal streaming models. This allows to make any convolutional model compatible with real-time buffer-based processing. As our method is based on a post-training reconfiguration of the model, we show that it is able to transform models trained without causal constraints into streaming models. We apply our method on the recent RAVE model as a case study. This model provides high-quality real-time audio synthesis on a wide range of signals and thus is an ideal candidate to evaluate our method. It should be noted that our method is not restricted to RAVE, and can be straightforwardly applied to any convolutional network. We test our approach on multiple music and speech datasets and show that it is faster than overlap-add methods, while having no impact on the generation quality. Finally, we introduce two open-source implementation of our work as Max/MSP and PureData externals, and as a VST audio plugin. This allows to endow traditional digital audio workstations with real-time neural audio synthesis.
Download Antiderivative Antialiasing with Frequency Compensation for Stateful Systems Employing nonlinear functions in audio DSP algorithms requires attention as they generally introduce aliasing. Among others, antiderivative antialiasing proved to be an effective method for static nonlinearities and gave rise to a number of variants, including our AA-IIR method. In this paper we introduce an improvement to AA-IIR that makes it suitable for use in stateful systems. Indeed, employing standard antiderivative antialiasing techniques in such systems alters their frequency response and may cause stability issues. Our method consists in cascading a digital filter after the AA-IIR block in order to fully compensate for unwanted delay and frequency-dependent effects. We study the conditions for such a digital filter to be stable itself and evaluate the method by applying it to the diode clipper circuit.
Download Deforming the Oscillator: Iterative Phases Over Parametrizable Closed Paths Iterative phase formulations allow for the generalization of many oscillatory sound synthesis methods from circles to general parametrizable loops, with or without explicit geometric contexts. This paper describes this approach, leading to the ability to perform modulation, feedback and chaotic oscillations over deformed circles that can include ill-behaved geometries, while allowing modulations or feedback to be deformed as well.
Download Higher-Order Scattering Delay Networksfor Artificial Reverberation Computer simulations of room acoustics suffer from an efficiency vs accuracy trade-off, with highly accurate wave-based models being highly computationally expensive, and delay-network-based models lacking in physical accuracy. The Scattering Delay Network (SDN) is a highly efficient recursive structure that renders first order reflections exactly while approximating higher order ones. With the purpose of improving the accuracy of SDNs, in this paper, several variations on SDNs are investigated, including appropriate node placement for exact modeling of higher order reflections, redesigned scattering matrices for physically-motivated scattering, and pruned network connections for reduced computational complexity. The results of these variations are compared to state-of-the-art geometric acoustic models for different shoebox room simulations. Objective measures (Normalized Echo Densities (NEDs) and Energy Decay Curves (EDCs)) showed a close match between the proposed methods and the references. A formal listening test was carried out to evaluate differences in perceived naturalness of the synthesized Room Impulse Responses. Results show that increasing SDNs’ order and adding directional scattering in a fully-connected network improves perceived naturalness, and higher-order pruned networks give similar performance at a much lower computational cost.
Download Multichannel Interleaved Velvet Noise The cross-correlation of multichannel reverberation generated using interleaved velvet noise is studied. The interleaved velvetnoise reverberator was proposed recently for synthesizing the late reverb of an acoustic space. In addition to providing a computationally efficient structure and a perceptually smooth response, the interleaving method allows combining its independent branch outputs in different permutations, which are all equally smooth and flutter-free. For instance, a four-branch output can be combined in 4! or 24 ways. Additionally, each branch output set is mixed orthogonally, which increases the number of permutations from M ! to M 2 !, since sign inversions are taken along. Using specific matrices for this operation, which change the sign of velvet-noise sequences, decreases the correlation of some of the combinations. This paper shows that many selections of permutations offer a set of well decorrelated output channels, which produce a diffuse and colorless sound field, which is validated with spatial variation. The results of this work can be applied in the design of computationally efficient multichannel reverberators.
Download Improved Automatic Instrumentation Role Classification and Loop Activation Transcription Many electronic music (EM) genres are composed through the activation of short audio recordings of instruments designed for seamless repetition—or loops. In this work, loops of key structural groups such as bass, percussive or melodic elements are labelled by the role they occupy in a piece of music through the task of automatic instrumentation role classification (AIRC). Such labels assist EM producers in the identification of compatible loops in large unstructured audio databases. While human annotation is often laborious, automatic classification allows for fast and scalable generation of these labels. We experiment with several deeplearning architectures and propose a data augmentation method for improving multi-label representation to balance classes within the Freesound Loop Dataset. To improve the classification accuracy of the architectures, we also evaluate different pooling operations. Results indicate that in combination with the data augmentation and pooling strategies, the proposed system achieves state-of-theart performance for AIRC. Additionally, we demonstrate how our proposed AIRC method is useful for analysing the structure of EM compositions through loop activation transcription.
Download Joint Estimation of Fader and Equalizer Gains of DJ Mixers Using Convex Optimization Disc jockeys (DJs) use audio effects to make a smooth transition from one song to another. There have been attempts to computationally analyze the creative process of seamless mixing. However, only a few studies estimated fader or equalizer (EQ) gains controlled by DJs. In this study, we propose a method that jointly estimates time-varying fader and EQ gains so as to reproduce the mix from individual source tracks. The method approximates the equalizer filters with a linear combination of a fixed equalizer filter and a constant gain to convert the joint estimation into a convex optimization problem. For the experiment, we collected a new DJ mix dataset that consists of 5,040 real-world DJ mixes with 50,742 transitions, and evaluated the proposed method with a mix reconstruction error. The result shows that the proposed method estimates the time-varying fader and equalizer gains more accurately than existing methods and simple baselines.
Download Time-Varying Filter Stability and State Matrix Products We show a new sufficient criterion for time-varying digital filter stability: that the matrix norm of the product of state matrices over a certain finite number of time steps is bounded by 1. This extends Laroche’s Criterion 1, which only considered one time step, while hinting at extensions to two time steps. Further extending these results, we also show that there is no intrinsic requirement that filter coefficients be frozen over any time scale, and extend to any dimension a helpful theorem that allows us to avoid explicitly performing eigen- or singular value decompositions in studying the matrix norm. We give a number of case studies on filters known to be time-varying stable, that cannot be proven time-varying stable with the original criterion, where the new criterion succeeds.
Download Flutter Echo Modeling Flutter echo is a well-known acoustic phenomenon that occurs when sound waves bounce between two parallel reflective surfaces, creating a repetitive sound. In this work, we introduce a method to recreate flutter echo as an audio effect. The proposed algorithm is based on a feedback structure utilizing velvet noise that aims to synthesize the fluttery components of a reference room impulse response presenting flutter echo. Among these, the repetition time defines the length of the delay line in a feedback filter. The specific spectral properties of the flutter are obtained with a bandpass attenuation filter and a ripple filter, which enhances the harmonic behavior of the sound. Additional temporal shaping of a velvet-noise filter, which processes the output of the feedback loop, is performed based on the properties of the reference flutter. The comparison between synthetic and measured flutter echo impulse responses shows good agreement in terms of both the repetition time and reverberation time values.