Paper Archive

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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This paper introduces Wave Pulse Phase Modulation (WPPM), a novel synthesis technique based on phase shaping. It combines two classic digital synthesis techniques: Phase Modulation (PM) and Phase Distortion (PD), aiming to overcome their respective limitations while enabling the creation of new, interesting timbres. It works by segmenting a phase signal into two regions, each independently driving the phase of a modulator waveform. This results in two distinct pulses per period that together form the signal used as the phase input to a carrier waveform, similar to PM, hence the name Wave Pulse Phase Modulation. This method provides a minimal set of parameters that enable the creation of complex, evolving waveforms, and rich dynamic textures. By modulating these parameters, WPPM can produce a wide range of interesting spectra, including those with formant-like resonant peaks. The paper examines PM and PD in detail, exploring the modifications needed to integrate them with WPPM, before presenting the full WPPM algorithm alongside its parameters and creative possibilities. Finally, it discusses scope for further research and developments into new similar phase shaping algorithms.

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This paper introduces a digital reconstruction of the morphophone, a complex magnetophonic device developed in the 1950s within the laboratories of the GRM (Groupe de Recherches Musicales) in Paris. The analysis, design, and implementation methodologies underlying the Digital Morphophone Environment are discussed. Based on a detailed review of historical sources and limited documentation – including a small body of literature and, most notably, archival images – the core operational principles of the morphophone have been modeled within the MAX visual programming environment. The main goals of this work are, on the one hand, to study and make accessible a now obsolete and unavailable tool, and on the other, to provide the opportunity for new explorations in computer music and research.

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Recently, differentiable multiple-input multiple-output Feedback Delay Networks (FDNs) have been proposed for modeling target multichannel room impulse responses by optimizing their parameters according to perceptually-driven time-domain descriptors. However, in spatial audio applications, frequency-domain characteristics and inter-channel differences are crucial for accurately replicating a given soundfield. In this article, targeting the modeling of the response of higher-order microphone arrays, we improve on the methodology by optimizing the FDN parameters using a novel spatially-informed loss function, demonstrating its superior performance over previous approaches and paving the way toward the use of differentiable FDNs in spatial audio applications such as soundfield reconstruction and rendering.

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The creation of personal sound zones is an effective solution for delivering personalized auditory experiences in shared spaces. Their applications span various domains, including in-car entertainment, home and office environments, and healthcare functions. This paper presents a novel approach for the creation of personal sound zones using a modified algorithm for multi-lobe control in loudspeaker line array. The proposed method integrates a pressurematching beamforming algorithm with an innovative technique for reducing side lobes, enhancing the precision and isolation of sound zones. The system was evaluated through simulations and experimental tests conducted in a semi-anechoic environment and a large listening room. Results demonstrate the effectiveness of the method in creating two separate sound zones.

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The common-slope model is used to model late reverberation of complex room geometries such as multiple coupled rooms. The model fits band-limited room impulse responses using a set of common decay rates, with amplitudes varying based on listener positions. This paper investigates amplitude estimation methods within the common-slope model framework. We compare several traditional least squares estimation methods and propose using LINEX regression, a Maximum Likelihood approach using logsquared RIR statistics. Through statistical analysis and simulation tests, we demonstrate that LINEX regression improves accuracy and reduces bias when compared to traditional methods.

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Scattering delay networks (SDNs) provide a flexible and efficient framework for artificial reverberation and room acoustic modeling. In this work, we introduce a differentiable SDN, enabling gradient-based optimization of its parameters to better approximate the acoustics of real-world environments. By formulating key parameters such as scattering matrices and absorption filters as differentiable functions, we employ gradient descent to optimize an SDN based on a target room impulse response. Our approach minimizes discrepancies in perceptually relevant acoustic features, such as energy decay and frequency-dependent reverberation times. Experimental results demonstrate that the learned SDN configurations significantly improve the accuracy of synthetic reverberation, highlighting the potential of data-driven room acoustic modeling.

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We introduce a novel method for designing attenuation filters in digital audio reverberation systems based on Feedback Delay Networks (FDNs). Our approach uses Second Order Sections (SOS) of Infinite Impulse Response (IIR) filters arranged as parametric equalizers (PEQ), enabling fine control over frequency-dependent reverberation decay. Unlike traditional graphic equalizer designs, which require numerous filters per delay line, we propose a scalable solution where the number of filters can be adjusted. The frequency, gain, and quality factor (Q) parameters are shared parameters across delay lines and only the gain is adjusted based on delay length. This design not only reduces the number of optimization parameters, but also remains fully differentiable and compatible with gradient-based learning frameworks. Leveraging principles of analog filter design, our method allows for efficient and accurate filter fitting using supervised learning. Our method delivers a flexible and differentiable design, achieving state-of-the-art performance while significantly reducing computational cost.

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Decorrelation filters transform mono audio into multiple decorrelated copies. This paper introduces a novel decorrelation filter design based on a resonator bank, which produces a sum of over a thousand exponentially decaying sinusoids. A headphone listening test was used to identify the minimum inter-channel time delays that perceptually match ERB-filtered coherent noise to corresponding incoherent noise. The decay rate of each resonator is set based on a group delay profile determined by the listening test results at its corresponding frequency. Furthermore, the delays from the test are used to refine frequency-dependent windowing in coherence estimation, which we argue represents the perceptually most accurate way of assessing interaural coherence. This coherence measure then guides an optimization process that adjusts the initial phases of the sinusoids to minimize the coherence between two instances of the resonator-based decorrelator. The delay results establish the necessary group delay per ERB for effective decorrelation, revealing higher-than-expected values, particularly at higher frequencies. For comparison, the optimization is also performed using two previously proposed group-delay profiles: one based on the period of the ERB band center frequency and another based on the maximum group-delay limit before introducing smearing. The results indicate that the perceptually informed profile achieves equal decorrelation to the latter profile while smearing less at high frequencies. Overall, optimizing the phase response of the proposed decorrelator yields significantly lower coherence compared to using a random phase.

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We present a spline-based method for compressing and reconstructing Head-Related Transfer Functions (HRTFs) that preserves perceptual quality. Our approach focuses on the magnitude response and consists of four stages: (1) acquiring minimumphase head-related impulse responses (HRIR), (2) transforming them into the frequency domain and applying adaptive Wiener filtering to preserve important spectral features, (3) extracting a minimal set of control points using derivative-based methods to identify local maxima and inflection points, and (4) reconstructing the HRTF using piecewise cubic Hermite interpolation (PCHIP) over the refined control points. Evaluation on 301 subjects demonstrates that our method achieves an average compression ratio of 4.7:1 with spectral distortion ≤ 1.0 dB in each Equivalent Rectangular Band (ERB). The method preserves binaural cues with a mean absolute interaural level difference (ILD) error of 0.10 dB. Our method achieves about three times the compression obtained with a PCA-based method.

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