Paper Archive

Antiderivative Antialiasing (ADAA), has become a pivotal method for reducing aliasing when dealing with nonlinear function at audio rate. However, its implementation requires analytical computation of the antiderivative of the nonlinear function, which in practical cases can be challenging without a symbolic solver. Moreover, when the nonlinear function is given by measurements it must be approximated to get a symbolic description. In this paper, we propose a simple approach to ADAA for practical applications that employs numerical integration of lookup tables (LUTs) to approximate the antiderivative. This method eliminates the need for closed-form solutions, streamlining the ADAA implementation process in industrial applications. We analyze the trade-offs of this approach, highlighting its computational efficiency and ease of implementation while discussing the potential impact of numerical integration errors on aliasing performance. Experiments are conducted with static nonlinearities (tanh, a simple wavefolder and the Buchla 259 wavefolding circuit) and a stateful nonlinear system (the diode clipper).

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Several methods exist in the literature to accurately simulate Bucket Brigade Device (BBD) chips, which are widely used in analog delay-based audio effects for their characteristic lo-fi sound, which is affected by noise, nonlinearities and aliasing. The latter is a desired quality, being typical of those chips. However, when simulating BBDs in a discrete-time domain environment, additional aliasing components occur that need to be suppressed. In this work, we propose a novel method that applies the Bandlimited Step (BLEP) technique, effectively minimizing aliasing artifacts introduced by the simulation. The paper provides some insights on the design of a BBD simulation using interpolation at the input for clock rate conversion and, most importantly, shows how BLEP can be effective in reducing unwanted aliasing artifacts. Interpolation is shown to have minor importance in the reduction of spurious components.

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The acoustic piano and its sound production mechanisms have been extensively studied in the field of acoustics. Similarly, digital piano synthesis has been the focus of numerous signal processing research studies. However, the role of the piano action in shaping the dynamics and nuances of piano sound has received less attention, particularly in the context of digital pianos. Digital pianos are well-established commercial instruments that typically use weighted keys with two or three sensors to measure the average key velocity—this being the only input to a sampling synthesis engine. In this study, we investigate whether this simplified measurement method adequately captures the full dynamic behavior of the original piano action. After a brief review of the state of the art, we describe an experimental setup designed to measure physical properties of the keys and hammers of a piano. This setup enables high-precision readings of acceleration, velocity, and position for both the key and hammer across various dynamic levels. Through extensive data analysis, we examine their relationships and identify the optimal key position for velocity measurement. We also analyze a digital piano key to determine where the average key velocity is measured and compare it with our proposed optimal timing. We find that the instantaneous key velocity just before let-off correlates most strongly with hammer impact velocity, indicating a target for improved sensing; however, due to the limitations of discrete velocity sensing this optimization alone may not suffice to replicate the nuanced expressiveness of acoustic piano touch. This study represents the first step in a broader research effort aimed at linking piano touch, dynamics, and sound production.

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Traditional screen-based graphical user interfaces (GUIs) pose significant accessibility challenges for visually impaired users. This paper demonstrates how existing GUI elements can be translated into an interactive auditory domain using high-order Ambisonics and inertial sensor-based head tracking, culminating in a realtime binaural rendering over headphones. The proposed system is designed to spatialize the auditory output from VoiceOver, the built-in macOS screen reader, aiming to foster clearer mental mapping and enhanced navigability. A between-groups experiment was conducted to compare standard VoiceOver with the proposed spatialized version. Non visually-impaired participants (n = 32), with no visual access to the test interface, completed a list-based exploration and then attempted to reconstruct the UI solely from auditory cues. Experimental results indicate that the head-tracked group achieved a slightly higher accuracy in reconstructing the interface, while user experience assessments showed no significant differences in self-reported workload or usability. These findings suggest that potential benefits may come from the integration of head-tracked binaural audio into mainstream screen-reader workflows, but future investigations involving blind and low-vision users are needed. Although the experimental testbed uses a generic desktop app, our ultimate goal is to tackle the complex visual layouts of music-production software, where an head-tracked audio approach could benefit visually impaired producers and musicians navigating plug-in controls.

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