Physically informed car engine sound synthesis for virtual and augmented environments

The richness of crossmodal feedback in car driving makes it an engaging, complex, yet “natural” activity. Audition plays an important role, as the engine sound, perceived in the cabin, conveys relevant cues about the vehicle motion. In this paper, we introduce a procedural and physically informed model for synthetic combustion engine sound, as an effective, flexible and computationally efficient alternative to sample-based and analysis/resynthesis approaches. The sound model, currently being developed as Max/MSP external, has been integrated in GeneCars, a driving simulator environment for industrial sound design, and SkAT Studio, a demonstration framework for the rapid creation of audio processing workflows

Auralization of Air Vehicle Noise for Community Noise Assessment

This paper serves as an introduction to air vehicle noise auralization and documents the current state-of-the-art. Auralization of flyover noise considers the source, path, and receiver as part of a time marching simulation. Two approaches are offered; a time domain approach performs synthesis followed by propagation, while a frequency domain approach performs propagation followed by synthesis. Source noise description methods are offered for isolated and installed propulsion system and airframe noise sources for a wide range of air vehicles. Methods for synthesis of broadband, discrete tones, steady and unsteady periodic, and a periodic sources are presented, and propagation methods and receiver considerations are discussed. Auralizations applied to vehicles ranging from large transport aircraft to small unmanned aerial systems demonstrate current capabilities

Engine sound simulation and generation in driving simulator

Simulating a driving environment that provides engine sound as auditory feedback to the driver is a challenging task due to the complexity of engine sound, a wide range of operating speeds, and repeated sound clicking during playback. This thesis describes a method of engine sound simulation and generation for a driving simulator. By analyzing sample sounds, spectral modeling synthesis was used to decompose the sound samples into deterministic and stochastic components. Then, the modeled deterministic and stochastic signals were employed to resynthesize the sounds. To represent engine sounds not available in the recorded database, sound interpolation was applied to two neighboring engine sounds. In addition, a cancelation method was developed to remove the repeated clicking that occurs when engine sounds are played in a loop. Finally, a powertrain model was used to calculate the engine speed. As seen by comparing the spectrograms of the sounds, the resynthesized sounds exhibited high similarity to the recorded sample sounds. Also, the spectrogram of the sound generated by interpolating two sample sounds was found to agree fairly well with the actual engine sound --Abstract, page iii

Research and Development on Noise, Vibration, and Harshness of Road Vehicles Using Driving Simulators - A Review

Noise, vibration, and harshness (NVH) is a key aspect in the vehicle development. Reducing noise and vibration to create a comfortable environment is one of the main objectives in vehicle design. In the literature, many theoretical and experimental methods have been presented for improving the NVH performances of vehicles. However, in the great majority of situations, physical prototypes are still required as NVH is highly dependent on subjective human perception and a pure computational approach often does not suffice. In this article, driving simulators are discussed as a tool to reduce the need of physical prototypes allowing a reduction in development time while providing a deep understanding of vehicle NVH characteristics. The present article provides a review of the current development of driving simulator focused on problems, challenges, and solutions for NVH applications. Starting from the definition of the human response to noise and vibration, this article describes the different driving simulator technologies to tackle all the involved perception aspects. The different available technologies are discussed and compared as to provide design engineers with a complete picture of the current possibilities and future trends

Improving acoustic vehicle classification by information fusion

We present an information fusion approach for ground vehicle classification based on the emitted acoustic signal. Many acoustic factors can contribute to the classification accuracy of working ground vehicles. Classification relying on a single feature set may lose some useful information if its underlying sound production model is not comprehensive. To improve classification accuracy, we consider an information fusion diagram, in which various aspects of an acoustic signature are taken into account and emphasized separately by two different feature extraction methods. The first set of features aims to represent internal sound production, and a number of harmonic components are extracted to characterize the factors related to the vehicle’s resonance. The second set of features is extracted based on a computationally effective discriminatory analysis, and a group of key frequency components are selected by mutual information, accounting for the sound production from the vehicle’s exterior parts. In correspondence with this structure, we further put forward a modifiedBayesian fusion algorithm, which takes advantage of matching each specific feature set with its favored classifier. To assess the proposed approach, experiments are carried out based on a data set containing acoustic signals from different types of vehicles. Results indicate that the fusion approach can effectively increase classification accuracy compared to that achieved using each individual features set alone. The Bayesian-based decision level fusion is found fusion is found to be improved than a feature level fusion approac

Timbre from Sound Synthesis and High-level Control Perspectives

International audienceExploring the many surprising facets of timbre through sound manipulations has been a common practice among composers and instrument makers of all times. The digital era radically changed the approach to sounds thanks to the unlimited possibilities offered by computers that made it possible to investigate sounds without physical constraints. In this chapter we describe investigations on timbre based on the analysis by synthesis approach that consists in using digital synthesis algorithms to reproduce sounds and further modify the parameters of the algorithms to investigate their perceptual relevance. In the first part of the chapter timbre is investigated in a musical context. An examination of the sound quality of different wood species for xylophone making is first presented. Then the influence of instrumental control on timbre is described in the case of clarinet and cello performances. In the second part of the chapter, we mainly focus on the identification of sound morphologies, so called invariant sound structures responsible for the evocations induced by environmental sounds by relating basic signal descriptors and timbre descriptors to evocations in the case of car door noises, motor noises, solid objects, and their interactions

How should an electric vehicle sound? User and expert perception

International audienc