Analysis-Driven Procedural Generation of an Engine Sound Dataset with Embedded Control Annotations
Computational engine sound modeling is central to the automotive audio industry, particularly for active sound design applications and virtual prototyping. Emerging data-driven engine sound synthesis methods require large volumes of standardized, clean audio recordings with precisely time-aligned operating-state annotations: data that is difficult to obtain due to high costs, specialized measurement equipment requirements, and inevitable noise contamination. We present an analysis-driven framework for generating engine audio with sample-accurate control annotations. The method extracts harmonic structures from real recordings through pitch-adaptive spectral analysis, which then drive an e...
| Authors | Robin Doerfler, Lonce Wyse |
|---|---|
| Primary category | cs.SD |
| Published | 8 March 2026 |
| Last updated at source | 2 June 2026 |
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