3 papers
cs.SD2026
Gradient-Based Learning of Parametric Engine Sound Representations for Real-Time Resynthesis and Tuning on Embedded Systems
Robin Doerfler, Matthieu Kuntz, Clemens Zimmer
Engine order enhancement is central in automotive sound design, where selective harmonics are synthesized to shape perceptual qualities such as sportiness, refinedness, or power. T…
cs.SD2026
Physics-Informed Neural Engine Sound Modeling with Differentiable Pulse-Train Synthesis
Robin Doerfler, Lonce Wyse
Engine sounds originate from sequential exhaust pressure pulses rather than sustained harmonic oscillations. While neural synthesis methods typically aim to approximate the resulti…
cs.SD2026
Analysis-Driven Procedural Generation of an Engine Sound Dataset with Embedded Control Annotations
Robin Doerfler, Lonce Wyse
Computational engine sound modeling is central to the automotive audio industry, particularly for active sound design applications and virtual prototyping. Emerging data-driven eng…