Some factors influencing the intelligibility of the enhanced whisper in the joint time-frequency domain are evaluated. Specifically, both the spectrum density and different regions of the enhanced spectrum are analyze...Some factors influencing the intelligibility of the enhanced whisper in the joint time-frequency domain are evaluated. Specifically, both the spectrum density and different regions of the enhanced spectrum are analyzed. Experimental results show that for a spectrum of some density, the joint time-frequency gain-modification based speech enhancement algorithm achieves significant improvement in intelligibility. Additionally, the spectrum region where the estimated spectrum is smaller than the clean spectrum, is the most important region contributing to intelligibility improvement for the enhanced whisper. The spectrum region where the estimated spectrum is larger than twice the size of the clean spectrum is detrimental to speech intelligibility perception within the whisper context.展开更多
A novel method is proposed to obtain the power spectra of hidden variables in a chaotic time series. By embedding the data in phase space , and recording the conditional probability density of points that the trajecto...A novel method is proposed to obtain the power spectra of hidden variables in a chaotic time series. By embedding the data in phase space , and recording the conditional probability density of points that the trajectory encounters as it evolves in the reconstructed phase space, it is possible to recover the power spectra of hidden variables in chaotic time series through a spectral analysis over the conditional probability density time series. The method is robust in the application to Lorenz system, 4 dimension Rssler system and rigid body motion by linear feedback system (LFRBM). Applying the method to the time series of sea surface temperature (SST) of the South China Sea, we obtained the power spectra of the wind speed (WS) from SST data. Furthermore, the results showed that there exists an important nonlinear interaction between the SST and the WS.展开更多
基金The National Natural Science Foundation of China(No.61301295,61273266,61301219,61201326,61003131)the Natural Science Foundation of Anhui Province(No.1308085QF100,1408085MF113)+2 种基金the Natural Science Foundation of Jiangsu Province(No.BK20130241)the Natural Science Foundation of Higher Education Institutions of Jiangsu Province(No.12KJB510021)the Doctoral Fund of Anhui University
文摘Some factors influencing the intelligibility of the enhanced whisper in the joint time-frequency domain are evaluated. Specifically, both the spectrum density and different regions of the enhanced spectrum are analyzed. Experimental results show that for a spectrum of some density, the joint time-frequency gain-modification based speech enhancement algorithm achieves significant improvement in intelligibility. Additionally, the spectrum region where the estimated spectrum is smaller than the clean spectrum, is the most important region contributing to intelligibility improvement for the enhanced whisper. The spectrum region where the estimated spectrum is larger than twice the size of the clean spectrum is detrimental to speech intelligibility perception within the whisper context.
文摘A novel method is proposed to obtain the power spectra of hidden variables in a chaotic time series. By embedding the data in phase space , and recording the conditional probability density of points that the trajectory encounters as it evolves in the reconstructed phase space, it is possible to recover the power spectra of hidden variables in chaotic time series through a spectral analysis over the conditional probability density time series. The method is robust in the application to Lorenz system, 4 dimension Rssler system and rigid body motion by linear feedback system (LFRBM). Applying the method to the time series of sea surface temperature (SST) of the South China Sea, we obtained the power spectra of the wind speed (WS) from SST data. Furthermore, the results showed that there exists an important nonlinear interaction between the SST and the WS.
