In this work, a novel voice activity detection （VAD） algorithm that uses speech absence probability （SAP） based on Teager energy （TE） was proposed for speech enhancement. The proposed method employs local SAP （...In this work, a novel voice activity detection （VAD） algorithm that uses speech absence probability （SAP） based on Teager energy （TE） was proposed for speech enhancement. The proposed method employs local SAP （LSAP） based on the TE of noisy speech as a feature parameter for voice activity detection （VAD） in each frequency subband, rather than conventional LSAP. Results show that the TE operator can enhance the abiTity to discriminate speech and noise and further suppress noise components. Therefore, TE-based LSAP provides a better representation of LSAP, resulting in improved VAD for estimating noise power in a speech enhancement algorithm. In addition, the presented method utilizes TE-based global SAP （GSAP） derived in each frame as the weighting parameter for modifying the adopted TE operator and improving its performance. The proposed algorithm was evaluated by objective and subjective quality tests under various environments, and was shown to produce better results than the conventional method.展开更多
Based on minimum output energy,an improved blind multiuser detection algorithm is proposed by the use of Hopfield neural network.Compared with traditional algorithms,the proposed algorithm does not need the circuit fo...Based on minimum output energy,an improved blind multiuser detection algorithm is proposed by the use of Hopfield neural network.Compared with traditional algorithms,the proposed algorithm does not need the circuit for constraints.The resources are greatly saved and the complexity is reduced as well.The simulation results show that the performance of the improved algorithm is similar to that of the optimal multiuser detection algorithm which is not suitable for the mobile station.Compared with the traditional gradient blind multiuser detection algorithm,the convergence speed of the improved algorithm is quickened.展开更多
基金Project supported by Inha University Research GrantProject(10031764) supported by the Strategic Technology Development Program of Ministry of Knowledge Economy, Korea
文摘In this work, a novel voice activity detection （VAD） algorithm that uses speech absence probability （SAP） based on Teager energy （TE） was proposed for speech enhancement. The proposed method employs local SAP （LSAP） based on the TE of noisy speech as a feature parameter for voice activity detection （VAD） in each frequency subband, rather than conventional LSAP. Results show that the TE operator can enhance the abiTity to discriminate speech and noise and further suppress noise components. Therefore, TE-based LSAP provides a better representation of LSAP, resulting in improved VAD for estimating noise power in a speech enhancement algorithm. In addition, the presented method utilizes TE-based global SAP （GSAP） derived in each frame as the weighting parameter for modifying the adopted TE operator and improving its performance. The proposed algorithm was evaluated by objective and subjective quality tests under various environments, and was shown to produce better results than the conventional method.
基金Supported by China Postdoctoral Science Foundation(No.20060390170)Science and Technology Development Foundation of Tianjin University(No.20060610)
文摘Based on minimum output energy,an improved blind multiuser detection algorithm is proposed by the use of Hopfield neural network.Compared with traditional algorithms,the proposed algorithm does not need the circuit for constraints.The resources are greatly saved and the complexity is reduced as well.The simulation results show that the performance of the improved algorithm is similar to that of the optimal multiuser detection algorithm which is not suitable for the mobile station.Compared with the traditional gradient blind multiuser detection algorithm,the convergence speed of the improved algorithm is quickened.
