Search Results

As a key component of in-vehicle intelligent voice technology, speech enhancement can extract clean speech signals contaminated by environmental noise to improve the perceptual quality and intelligibility of speech. It has extensive applications in the field of intelligent car cabins. Although some end-to-end speech enhancement methods based on time domain have been proposed, there is often limited consideration given to designing model architectures based on the characteristics of the speech signal. In this paper, we propose a new U-Net based speech enhancement framework that utilizes the temporal correlation of speech signals to reconstruct higher-quality and more intelligible clean speech.

It is a worldwide technical difficulty to predict brake squeal uncertainty and its propagation regularity due to key parameters’ randomcity. However, as a widely used stochastic finite element method, Monte Carlo Method costs a large amount of time in calculation. It is very important to establish a fast prediction method for brake squeal uncertainty due to key parameters. In this paper, perturbation concept was applied for disc brake squeal uncertainty prediction. Firstly, a simplified, parameterized finite element model of disc brake was established for complex eigenvalues calculation. Then sensitivity analysis of real parts and frequencies of complex eigenvalues to influence parameters was carried out based on the finite element model. A series of second order perturbation polynomial formulas were fitted from the sensitivity analysis results, which were used for calculation of uncertain complex eigenvalues.