Sample-based engine noise synthesis using a harmonic synchronous overlap-and-add method (original) (raw)
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IEEE Transactions on Industrial Electronics, 2001
This paper presents a new method for modeling and synthesis of automotive engine sounds using a deterministic-stochastic signal decomposition approach. First, the deterministic component is extracted using a synchronous discrete Fourier transform method and this is subtracted out from the original signal. Next, the (residual) stochastic component is modeled (and synthesized) using a new multipulse excited time-series modeling technique. The effectiveness of the proposed methodology is demonstrated using recorded data sets of actual engine sounds. The results of both numerical and subjective assessment tests are presented.
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2002
Spectral synthesis techniques often use the OverLap-Add method. But in the case of noise synthesis, both experiments and theory show that this method introduces intensity fluctuations which imply audible artifacts. We propose here new methods to avoid these variations. The first one consists in multiplying the resulting signal by another weighting window to compensate dynamic fluctuations. The second one defines a new OLA weighting window. The third one concerns only noises synthesized with sinusoidal components and uses time-shifting to cancel artifacts.
Acta acustica, 2023
In traditional combustion engine vehicles, the sound of the engine plays an important role in enhancing the driver's experience of the vehicle's dynamics, and contributes to both comfort and safety. However, with the development of quieter electric vehicles, drivers no longer receive this important auditory feedback, and this can lead to a less satisfying acoustic environment in the vehicle cabin. To address this issue, sonification strategies have been developed for electric vehicles to provide similar auditory feedback to the driver, but feedback from users has suggested that the sounds produced by these strategies do not blend seamlessly with the other sounds in the vehicle cabin. This study focuses on identifying the key acoustic parameters that create a sense of cohesion between the synthetic sounds and the vehicle's natural soundscape, based on the characteristics of traditional combustion engine vehicles. Through analyzing the time and frequency of the noises produced by combustion engine vehicles, the presence of micro-modulations in both frequency and amplitude was identified, as well as resonances caused by the transfer of sound between the engine and the cabin. These parameters were incorporated into a synthesis model for the sonification of electric vehicle dynamics, based on the Shepard-Risset illusion. A perceptual test was conducted, and the results showed that the inclusion of resonances in the synthesized sounds significantly enhanced their naturalness, while micro-modulations had no significant impact.
Spectral-Based Analysis and Synthesis of Audio Signals
Technologies and Applications, 2007
This chapter reviews audio signal processing techniques related to sound generation via additive synthesis. Particular focus will be put on sinusoidal modeling. Each processing stage involved in obtaining a sinusoidal representation for audio signals is described. Then, synthesis techniques that allow reconstructing an audio signal based on a given parametric representation are presented. Finally, some audio applications where sinusoidal modeling is employed are briefly discussed.
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While the technique of auralization has been in use for quite some time in architectural acoustics, the application to environmental noise has been discovered only recently. With road traffic noise being the dominant noise source in most countries, particular interest lies in the synthesis of realistic pass-by sounds. This article describes an auralizator for pass-bys of accelerating passenger cars. The key element is a synthesizer that simulates the acoustical emission of different vehicles, driving on different surfaces, under different operating conditions. Audio signals for the emitted tire noise, as well as the propulsion noise are generated using spectral modeling synthesis, which gives complete control of the signal characteristics. The sound of propulsion is synthesized as a function of instantaneous engine speed, engine load and emission angle, whereas the sound of tires is created in dependence of vehicle speed and emission angle. The sound propagation is simulated by applying a series of time-variant digital filters. To obtain the corresponding steering parameters of the synthesizer, controlled experiments were carried out. The tire noise parameters were determined from coast-by measurements of passenger cars with idling engines. To obtain the propulsion noise parameters, measurements at different engine speeds, engine loads and emission angles were performed using a chassis dynamometer. The article shows how, from the measured data, the synthesizer parameters are calculated using audio signal processing.
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We describe a system for generating sounds in real-time. The input t o the system is a flow of parameter values. These values control t he frequency and amplitude of a bank of oscillators. The time between two sets of parameter values in the flow is much larger than the time between two samples of the resulting sound. The sound generation system must compute the instantaneous value of each oscillator and then sum the results. The main problem is then to get sufficient performance out of the computation of each instantaneous oscillator value. Sine tables were ruled o ut because they either r equire interpolation (which is slow) or massive amounts of memory (essentially one table for each frequency). A w ell-known formula e xists for incrementally computing the samples of an oscillator, g iven any frequency and any amplitude, with only one floating-point multiplication and one floating-point addition per sample. This formula has two major problems. The first is that the parameters are...
IEEE Transactions on Audio, Speech, and Language Processing, 2000
The inverse fast Fourier transform (IFFT) method is a time-frequency technique which was proposed to alleviate the complexity of the additive sound synthesis method in real-time applications. However, its application is limited by its inherent tradeoff between time and frequency resolutions, which are determined by the number of frequencies used for time-frequency processing. In a previous work, the authors proposed a frequency-refining technique for overcoming this frequency limitation, permitting achieving any time and frequency resolution using a small number of frequencies. In this correspondence we extend this work, by proposing a time-refining technique which permits overcoming the time resolution limitation for a given number of frequencies. Additionally, we propose an alternative to the frequency-refining technique proposed in our previous work, which requires about half the computations. The combination of these two results permits achieving any time and frequency resolution for any given number of frequencies. Using this property, we find the number of frequencies which minimizes the overall complexity. We do so considering two different application scenarios (i.e., offline sound design and online real-time synthesis). This results in a major complexity reduction in comparison with the design proposed in our previous work.
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