Analysis-Driven Procedural Generation of an Engine Sound Dataset with Embedded Control Annotations

ArXi:2603.07584v1 Announce Type: cross Computational engine sound modeling is central to the automotive audio industry, particularly for active sound design, virtual prototyping, and emerging data-driven engine sound synthesis methods. These applications 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.