About

Victor Zappi is an Assistant Professor at Northeastern University College of Arts, Media and Design within the Electrical and Computer Engineering department. He holds a PhD in Computer Science Engineering with a focus on Music Technology from Istituto Italiano di Tecnologia and Università degli Studi di Genova, earned in 2012. His research focuses on computational acoustics, digital musical instruments, speech synthesis, and virtual reality. Zappi's work involves exploring innovative interfaces and techniques for musical expression, including non-rigid musical interfaces, acoustic simulation models, and augmented virtual percussion instruments. His contributions aim to support the development of new musical interactions and technologies, emphasizing the modification and appropriation of digital musical instruments.

Research topics

• Computer Science
• Computer Security
• Mathematics
• Art
• Cognitive psychology
• Computer vision
• History
• Cognitive science
• Arithmetic
• Human–computer interaction
• Mathematical analysis
• Aesthetics
• Acoustics
• Physics
• Speech recognition
• Psychology
• Art history

Selected publications

• A 2.5-dimensional acoustic wave solver: Modeling simplified vocal tract geometries with reduced computational load

  The Journal of the Acoustical Society of America · 2026-04-01

  article

  High-fidelity three-dimensional (3D) wave solvers accurately simulate acoustic wave propagation in complex vocal tract geometries but are computationally demanding, limiting their usage in real-time applications. In contrast, low-dimensional models are efficient but limited to cylindrical tracts, neglecting higher-order modes in their frequency responses. This paper introduces a lightweight lumped two-dimensional (2.5D) solver that combines the efficiency of low-dimensional models with the accuracy of 3D approaches to model straight tracts constrained to mid-sagittal symmetry. Like 3D, the 2.5D model captures transverse wave propagation and accounts for higher-order modes. We validate the model by comparing its transfer functions and pressure distributions against those of a conventional two-dimensional (2D) solver and a high-fidelity 3D finite element model for six straight tract geometries of varying complexity. This analysis demonstrates the abilities and limitations of the proposed method. The results show that the 2.5D solver closely matches the 3D model's transfer functions up to 12 kHz, with correlation coefficients exceeding 0.8 for symmetric tracts. For asymmetric geometries, it still performs significantly better than the 2D model. Additionally, the 2.5D solver achieves over two orders of magnitude computational speed-up compared to the 3D model, offering a better trade-off between accuracy and efficiency for vocal tract acoustic modeling.

  PublisherDOI

• Neural audio instruments: epistemological and phenomenological perspectives on musical embodiment of deep learning

  Frontiers in Computer Science · 2025-08-20 · 1 citations

  articleOpen access1st authorCorresponding

  Neural Audio is a category of deep learning pipelines which output audio signals directly, in real-time scenarios of action-sound interactions. In this work, we examine how neural audio-based artificial intelligence, when embedded in digital musical instruments (DMIs), shapes embodied musical interaction. While DMIs have long struggled to match the physical immediacy of acoustic instruments, neural audio methods can magnify this challenge, requiring data collection, model training and deep theoretical knowledge that appear to push musicians toward symbolic or conceptual modes of engagement. Paradoxically, these same methods can also foster more embodied practices, by introducing opaque yet expressive behaviors that free performers from rigid technical models and encourage discovery through tactile, real-time experimentation. Drawing on established perspectives in DMI embodiment literature, as well as emerging neural-audio-focused efforts within the community, we highlight two seemingly conflicting aspects of these instruments: on one side, they inherit many “disembodying” traits known from DMIs; on the other, they open pathways reminiscent of acoustic phenomenology and soma, potentially restoring the close physical interplay often missed in digital performance.

  PublisherOA PDFDOI

• 2.5D Vocal Tract Modeling: Bridging Low-Dimensional Efficiency with 3D Accuracy

  2024-09-01

  article
  PublisherDOI

• Three-dimensional finite-difference time-domain acoustic analysis of simplified vocal tract shapes

  Interspeech 2022 · 2022 · 3 citations

  • Computer Science
  • Acoustics
  • Computer Science
  PublisherDOI

• The Hyper Drumhead: A Musical Instrument For The Audio/Visual Manipulation Of Sound Waves

  2022-07-21

  article1st authorCorresponding

  The Hyper Drumhead is a novel digital musical instrument that allows for the visualization and the manipulation of sound waves. At its core, a GPU-accelerated physical model computes in real-time the propagation of sound waves in two dimensions, allowing for the audio/visual simulation of massive domains. Every time the musician touches the surface of the instrument, an excitation signal is injected into the simulation domain, triggering wave propagation in all directions. By drawing boundaries in the domain and modifying the acoustic parameters of the simulated medium, the musician may generate and modulate reflections and resonances, effectively shaping the timbre of the resulting sound. In this short paper, we describe the main components of the instrument, including the control interface and the underlying numerical simulation.

  PublisherDOI

• From the Lab to the Stage:Practical Considerations on Designing Performances with Immersive Virtual Musical Instruments

  HAL (Le Centre pour la Communication Scientifique Directe) · 2022-01-01

  book-chapterOpen access1st authorCorresponding
  Publisher

• Integrating music‐based interventions with gamma‐frequency stimulation for Subjective Cognitive Decline and Mild Cognitive Impairment

  Alzheimer s & Dementia · 2022-12-01 · 1 citations

  article

  Abstract Background Alzheimer’s disease (AD) is characterized by disrupted, synchronous neural activity in the gamma‐band range (30‐100 Hz) and atypical cross‐frequency coupling between gamma and other bands of brain activity 1‐3 . In non‐human‐animal models, restoring aberrant gamma activity with non‐invasive gamma sensory stimulation remediates multiple pathophysiologies of AD (e.g., amyloid‐beta, tau tangles) and improves cognition 4,5 . While promising, gamma sensory stimulation may be difficult to use with human patients. We theorize that combining gamma sensory stimulation with natural music may increase the efficacy of gamma interventions for dementia, as music naturally drives gamma brain activity; engages multiple brain networks that are important for learning, memory, and reward processing; and music‐based interventions can reduce distress and agitation in older adults with dementia 6 . Method We developed a non‐invasive, gamma‐ and music‐based intervention for dementia, called SynchronyGamma (SynG). SynG delivers synchronized bursts of gamma‐frequency visual stimulation during natural music listening, cross‐frequency coupled to delta (0.5 – 4 Hz) and theta (4 – 8 Hz) visual rhythms, which adapt in real‐time to musical rhythms. In a preclinical experiment featuring older adults with and without Mild Cognitive Impairment (MCI) and Subjective Cognitive Decline (SCD) (N = 19 experimental group, 3 with MCI/SCD; N = 18 control group, 2 with MCI/SCD), we tested whether a single‐dose of music listening with SynG, relative to a control intervention, drives gamma neural activity; induces cross‐frequency coupling between delta, theta, and gamma brain activity; and improves cognition (e.g., delayed‐match‐to‐sample working‐memory task) Results SynG was found to drive scalp‐recorded gamma brain activity (p<0.05), and induce stronger cross‐frequency coupling, relative to the control condition (p<0.05). Additionally, enhanced gamma activity was observed during the working‐memory task that followed the intervention. Finally, SynG participants performed more accurately on a visual working memory task compared to their control counterparts, although this improvement fell short of statistical significance following a single dose (p>0.05). Conclusion Together, these findings suggest that combining self‐selected music with delta, theta, and gamma frequency visual stimulation is effective at driving gamma neural activity, inducing cross‐frequency coupling, and it may improve cognitive functioning. Future research will assess the effects of a longitudinal implementation of the intervention.

  PublisherDOI

• Bodily Awareness Through NIMEs: Deautomatising Music Making Processes

  NIME 2022 · 2022 · 3 citations

  Senior authorCorresponding
  • Computer Science
  • Computer Science
  • Cognitive science

  The lived body, or soma, is the designation for the phenomenological experience of being a body, rather than simply a corporeal entity. Bodily knowledge, which evolves through bodily awareness, carries the lived body’s reflectivity. In this paper, such considerations are put in the context of previous work at NIME, specifically that revolving around with the vocal tract or the voice, due to its singular relation with embodiment. We understand that focusing on somaesthetics allows for novel ways of engaging with technology as well as highlighting biases that might go unnoticed otherwise. We present an inexpensive application of a respiration sensor that emerges from the aforementioned conceptualisations. Lastly, we reflect on how to better frame the role of bodily awareness in NIME.

  PublisherOA PDFDOI

• From the Lab to the Stage: Practical Considerations on Designing Performances with Immersive Virtual Musical Instruments

  Human-computer interaction series · 2022-10-13 · 2 citations

  book-chapterOpen access1st authorCorresponding

  Abstract Immersive virtual musical instruments (IVMIs) lie at the intersection between music technology and virtual reality. Being both digital musical instruments (DMIs) and elements of virtual environments (VEs), IVMIs have the potential to transport the musician into a world of imagination and unprecedented musical expression. But when the final aim is to perform live on stage, the employment of these technologies is anything but straightforward, for sharing the virtual musical experience with the audience gets quite arduous. In this chapter, we assess in detail the several technical and conceptual challenges linked to the composition of IVMI performances on stage, i.e., their scenography , providing a new critical perspective on IVMI performance and design. We first propose a set of dimensions meant to analyse IVMI scenographies, as well as to evaluate their compatibility with different instrument metaphors and performance rationales. Such dimensions are built from the specifics and constraints of DMIs and VEs; they include the level of immersion of musicians and spectators and provide an insight into the interaction techniques afforded by 3D user interfaces in the context of musical expression. We then analyse a number of existing IVMIs and stage setups, and finally suggest new ones, with the aim to facilitate the design of future immersive performances.

  PublisherOA PDFDOI

• A comparative study of two-dimensional vocal tract acoustic modeling based on Finite-Difference Time-Domain methods

  arXiv (Cornell University) · 2021-02-09 · 1 citations

  preprintOpen access

  The two-dimensional (2D) numerical approaches for vocal tract (VT) modelling can afford a better balance between the low computational cost and accurate rendering of acoustic wave propagation. However, they require a high spatio-temporal resolution in the numerical scheme for a precise estimation of acoustic formants at the simulation run-time expense. We have recently proposed a new VT acoustic modelling technique, known as the 2.5D Finite-Difference Time-Domain (2.5D FDTD), which extends the existing 2D FDTD approach by adding tube depth to its acoustic wave solver. In this work, first, the simulated acoustic outputs of our new model are shown to be comparable with the 2D FDTD and a realistic 3D FEM VT model at a low spatio-temporal resolution. Next, a radiation model is developed by including a circular baffle around the VT as head geometry. The transfer functions of the radiation model are analyzed using five different vocal tract shapes for vowel sounds /a/, /e/, /i/, /o/ and /u/.

  PublisherOA PDFDOI

Frequent coauthors

• Sidney Fels

  Stavros Niarchos Foundation

  11 shared

• Andrea Brogni

  Scuola Normale Superiore

  9 shared

• Darwin G. Caldwell

  9 shared

• Dario Mazzanti

  Italian Institute of Technology

  5 shared

• Marco Gaudina

  University of Genoa

  4 shared

• Andrew S. Allen

  4 shared

• Andrew McPherson

  Imperial College London

  4 shared

• Debasish Ray Mohapatra

  4 shared

Awards & honors

• Best Paper Award, 43rd International Computer Music Conferen…