The traffic spectra influence on indoor noise through windows is evaluated with laboratory and field measurements. Different traffic noise spectra were registered and reproduced, simulating the outdoor traffic conditi...The traffic spectra influence on indoor noise through windows is evaluated with laboratory and field measurements. Different traffic noise spectra were registered and reproduced, simulating the outdoor traffic conditions through different windows. Spectrum adaptation terms for the recorded spectra were different from the ones obtained from the Standards, showing that Normative gives a safe evaluation of the Weighted Sound Insulation Index. In field measurements, the level abatements calculated from the Facade Acoustic Insulation Index corrected with the adaptation terms shows that the ones from the Standard do not give a good approximation, while if the level abatements is calculated using the adaptation terms from the registered spectra, a more reliable approximation is achieved. Furthermore, comparing the level abatements for two windows having both Rw equal to 41 dB, very different values were obtained at different frequencies; therefore to characterize acoustic performances of windows, sound insulation curves are also needed. The correlation between the mean difference between adaptation terms calculated from the standard and the one between abatements obtained with pink noise and the ones obtained with the registered spectra is good, but different for road traffic and trains. In both, the difference diminishes when the difference between the abatements increases.展开更多
This paper improves and presents an advanced method of the voice conversion system based on Gaussian Mixture Models(GMM) models by changing the time-scale of speech.The Speech Transformation and Representation using A...This paper improves and presents an advanced method of the voice conversion system based on Gaussian Mixture Models(GMM) models by changing the time-scale of speech.The Speech Transformation and Representation using Adaptive Interpolation of weiGHTed spectrum(STRAIGHT) model is adopted to extract the spectrum features,and the GMM models are trained to generate the conversion function.The spectrum features of a source speech will be converted by the conversion function.The time-scale of speech is changed by extracting the converted features and adding to the spectrum.The conversion voice was evaluated by subjective and objective measurements.The results confirm that the transformed speech not only approximates the characteristics of the target speaker,but also more natural and more intelligible.展开更多
文摘The traffic spectra influence on indoor noise through windows is evaluated with laboratory and field measurements. Different traffic noise spectra were registered and reproduced, simulating the outdoor traffic conditions through different windows. Spectrum adaptation terms for the recorded spectra were different from the ones obtained from the Standards, showing that Normative gives a safe evaluation of the Weighted Sound Insulation Index. In field measurements, the level abatements calculated from the Facade Acoustic Insulation Index corrected with the adaptation terms shows that the ones from the Standard do not give a good approximation, while if the level abatements is calculated using the adaptation terms from the registered spectra, a more reliable approximation is achieved. Furthermore, comparing the level abatements for two windows having both Rw equal to 41 dB, very different values were obtained at different frequencies; therefore to characterize acoustic performances of windows, sound insulation curves are also needed. The correlation between the mean difference between adaptation terms calculated from the standard and the one between abatements obtained with pink noise and the ones obtained with the registered spectra is good, but different for road traffic and trains. In both, the difference diminishes when the difference between the abatements increases.
基金Supported by the National Natural Science Foundation of China (No. 60872105)the Program for Science & Technology Innovative Research Team of Qing Lan Project in Higher Educational Institutions of Jiangsuthe Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD)
文摘This paper improves and presents an advanced method of the voice conversion system based on Gaussian Mixture Models(GMM) models by changing the time-scale of speech.The Speech Transformation and Representation using Adaptive Interpolation of weiGHTed spectrum(STRAIGHT) model is adopted to extract the spectrum features,and the GMM models are trained to generate the conversion function.The spectrum features of a source speech will be converted by the conversion function.The time-scale of speech is changed by extracting the converted features and adding to the spectrum.The conversion voice was evaluated by subjective and objective measurements.The results confirm that the transformed speech not only approximates the characteristics of the target speaker,but also more natural and more intelligible.
