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      Application of Generative Adversarial Nets (GANs) in Active Sound Production System of Electric Automobiles

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      Shock and Vibration

      Hindawi Limited

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          Abstract

          To improve the diversity and quality of sound mimicry of electric automobile engines, a generative adversarial network (GAN) model was used to construct an active sound production model for electric automobiles. The structure of each layer in the network in this model and the size of its convolution kernel were designed. The gradient descent in network training was optimized using the adaptive moment estimation (Adam) algorithm. To demonstrate the quality difference of the generated samples from different input signals, two GAN models with different inputs were constructed. The experimental results indicate that the model can accurately learn the characteristic distributions of raw audio signals. Results from a human ear auditory test show that the generated audio samples mimicked the real samples well, and a leave-one-out (LOO) test show that the diversity of the samples generated from the raw audio signals was higher than that of samples generated from a two-dimensional spectrogram.

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          Most cited references 5

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          Deconvolution and Checkerboard Artifacts

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            Artificial Engine Sound Synthesis Method for Modification of the Acoustic Characteristics of Electric Vehicles

            Sound radiation from electric motor-driven vehicles is negligibly small compared to sound radiation from internal combustion engine automobiles. When running on a local road, an artificial sound is required as a warning signal for the safety of pedestrians. In this study, an engine sound was synthesized by combining artificial mechanical and combustion sounds. The mechanical sounds were made by summing harmonic components representing sounds from rotating engine cranks. The harmonic components, including not only magnitude but also phase due to frequency, were obtained by the numerical integration method. The combustion noise was simulated by random sounds with similar spectral characteristics to the measured value and its amplitude was synchronized by the rotating speed. Important parameters essential for the synthesized sound to be evaluated as radiation from actual engines were proposed. This approach enabled playing of sounds for arbitrary engines. The synthesized engine sounds were evaluated for recognizability of vehicle approach and sound impression through auditory experiments.
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              AI-GAN: Asynchronous interactive generative adversarial network for single image rain removal

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                Author and article information

                Contributors
                Journal
                Shock and Vibration
                Shock and Vibration
                Hindawi Limited
                1875-9203
                1070-9622
                October 28 2020
                October 28 2020
                : 2020
                : 1-10
                Affiliations
                [1 ]Information Technology Center, Luoyang Institute of Science &Technology, Luoyang 471023, China
                [2 ]School of Automotive and Transportation, Tianjin University of Technology and Education, Tianjin 300222, China
                [3 ]National Joint Engineering Research Center of Intelligent Vehicle Infrastructure Cooperation and Safety Technology, Tianjin University of Technology and Education, Tianjin 300222, China
                Article
                10.1155/2020/8888578
                0ca62820-5694-4bba-8910-c0604166effa
                © 2020

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