A machine learning based speech enhancement method is proposed to improve the intelligibility of whispered speech. A binary mask estimated by a two-class support vector machine （SVM） classifier is used to synthesize...A machine learning based speech enhancement method is proposed to improve the intelligibility of whispered speech. A binary mask estimated by a two-class support vector machine （SVM） classifier is used to synthesize the enhanced whisper. A novel noise robust feature called Gammatone feature cosine coefficients （GFCCs） extracted by an auditory periphery model is derived and used for the binary mask estimation. The intelligibility performance of the proposed method is evaluated and compared with the traditional speech enhancement methods. Objective and subjective evaluation results indicate that the proposed method can effectively improve the intelligibility of whispered speech which is contaminated by noise. Compared with the power subtract algorithm and the log-MMSE algorithm, both of which do not improve the intelligibility in lower signal-to-noise ratio （SNR） environments, the proposed method has good performance in improving the intelligibility of noisy whisper. Additionally, the intelligibility of the enhanced whispered speech using the proposed method also outperforms that of the corresponding unprocessed noisy whispered speech.展开更多
Compared to traditional rigid robots, soft robots, primarily made of deformable, or less rigid materials, have good adaptability, conformability and safety in interacting with the environment. Although soft robots hav...Compared to traditional rigid robots, soft robots, primarily made of deformable, or less rigid materials, have good adaptability, conformability and safety in interacting with the environment. Although soft robots have shown great potentials for extended applications and possibilities that are impossible or difficult for rigid body robots, it is of great importance for them to have the capability of controllable stiffness modulation. Stiffness modulation allows soft robots to have reversible change between the compliant, or flexible state and the rigid state. In this paper, we summarize existing principles and methods for stiffness modulation in soft robotic development and divide them into four groups based on their working principles. Acoustic-based methods have been proposed as the potential fifth group in stiffness modulation of soft robots. Initial design proposals based on the proposed acoustic method are presented, and challenges in further development are highlighted.展开更多
The noise of aerodynamics nature from modern transonic fan is examined from its sources with the perspective of noise reduction through aero-acoustics design using advanced Computational Fluid Dynamics (CFD) tools. In...The noise of aerodynamics nature from modern transonic fan is examined from its sources with the perspective of noise reduction through aero-acoustics design using advanced Computational Fluid Dynamics (CFD) tools. In particular the problems associated with the forward propagating noise in the front is addressed. It is identified that the shock wave spillage from the leading edge near the fan tip is the main source of the tone noise. Two different approaches have been studied to reduce the forward arc tone noise and two state-of-art transonic fans are designed using the strategies developed. The following rig tests show that while the fans exhibit other noise problems, the primary goals of noise reduction have been achieved through both fans and the novel noise reduction concept vindicated.展开更多
基金The National Natural Science Foundation of China (No.61231002,61273266,51075068,60872073,60975017, 61003131)the Ph.D.Programs Foundation of the Ministry of Education of China(No.20110092130004)+1 种基金the Science Foundation for Young Talents in the Educational Committee of Anhui Province(No. 2010SQRL018)the 211 Project of Anhui University(No.2009QN027B)
文摘A machine learning based speech enhancement method is proposed to improve the intelligibility of whispered speech. A binary mask estimated by a two-class support vector machine （SVM） classifier is used to synthesize the enhanced whisper. A novel noise robust feature called Gammatone feature cosine coefficients （GFCCs） extracted by an auditory periphery model is derived and used for the binary mask estimation. The intelligibility performance of the proposed method is evaluated and compared with the traditional speech enhancement methods. Objective and subjective evaluation results indicate that the proposed method can effectively improve the intelligibility of whispered speech which is contaminated by noise. Compared with the power subtract algorithm and the log-MMSE algorithm, both of which do not improve the intelligibility in lower signal-to-noise ratio （SNR） environments, the proposed method has good performance in improving the intelligibility of noisy whisper. Additionally, the intelligibility of the enhanced whispered speech using the proposed method also outperforms that of the corresponding unprocessed noisy whispered speech.
文摘Compared to traditional rigid robots, soft robots, primarily made of deformable, or less rigid materials, have good adaptability, conformability and safety in interacting with the environment. Although soft robots have shown great potentials for extended applications and possibilities that are impossible or difficult for rigid body robots, it is of great importance for them to have the capability of controllable stiffness modulation. Stiffness modulation allows soft robots to have reversible change between the compliant, or flexible state and the rigid state. In this paper, we summarize existing principles and methods for stiffness modulation in soft robotic development and divide them into four groups based on their working principles. Acoustic-based methods have been proposed as the potential fifth group in stiffness modulation of soft robots. Initial design proposals based on the proposed acoustic method are presented, and challenges in further development are highlighted.
文摘The noise of aerodynamics nature from modern transonic fan is examined from its sources with the perspective of noise reduction through aero-acoustics design using advanced Computational Fluid Dynamics (CFD) tools. In particular the problems associated with the forward propagating noise in the front is addressed. It is identified that the shock wave spillage from the leading edge near the fan tip is the main source of the tone noise. Two different approaches have been studied to reduce the forward arc tone noise and two state-of-art transonic fans are designed using the strategies developed. The following rig tests show that while the fans exhibit other noise problems, the primary goals of noise reduction have been achieved through both fans and the novel noise reduction concept vindicated.
