根据社会语言学理论,男性和女性的说话倾向性往往不同,其中增强语因与女性说话者联系在一起。本文旨在通过将美国电视连续剧“How I Met Your Mother”中的台词为语料,探索所选增强语在使用中的性别差异,包括在增强语选择和增强语搭配...根据社会语言学理论,男性和女性的说话倾向性往往不同,其中增强语因与女性说话者联系在一起。本文旨在通过将美国电视连续剧“How I Met Your Mother”中的台词为语料,探索所选增强语在使用中的性别差异,包括在增强语选择和增强语搭配方面的性别差异。由于副词增强语的比例较大,因此本文主要关注副词放大器的使用。展开更多
"Brevity is the soul of wit". 人们一向主张可以简洁为贵。然而“反复”(repetition)用之得当,则具有强调(emphasis)、鲜明突出(lucidity)等修辞功能,同时还富有韻律(rhythm)美。人们常用之以增强语势、烘托气氛,使重点更..."Brevity is the soul of wit". 人们一向主张可以简洁为贵。然而“反复”(repetition)用之得当,则具有强调(emphasis)、鲜明突出(lucidity)等修辞功能,同时还富有韻律(rhythm)美。人们常用之以增强语势、烘托气氛,使重点更突出、使典型形象更鲜明;也常用之以增添感染力、增强鼓动性,使强烈的感情更炽热、使消极的心绪更低沉,对此,笔者曾写过“【反复】在文学作品中的运用,一英语修辞文体谈”,着重讨论其修辞功能,本文试图对修辞性“反复”的诸多构成形式进行分类归纳,供修辞学者参考。展开更多
针对5G网络优化工作中出现的新空口承载语音(Voice over New Radio,VoNR)用户感知差的问题,探讨平均意见评分(Mean Opinion Score,MOS)值影响因素与分析流程,对后续出现的此类问题提供分析思路及具体解决方案。通过对网络现有参数和物...针对5G网络优化工作中出现的新空口承载语音(Voice over New Radio,VoNR)用户感知差的问题,探讨平均意见评分(Mean Opinion Score,MOS)值影响因素与分析流程,对后续出现的此类问题提供分析思路及具体解决方案。通过对网络现有参数和物理参数的核查,修改网络异常参数,以射频优化为基础、以参数优化为辅助,达到快速提升5G VoNR语音用户使用感知的目的。通过采用相应的网络优化手段,有效提升5G网络VoNR接通率,降低5G网络VoNR掉话率。展开更多
In order to improve the performance of general sidelobe canceller （GSC） based speech enhancement, a leakage constraints decision feedback generalized sidelobe canceller（LCDF-GSC） algorithm is proposed. The method ...In order to improve the performance of general sidelobe canceller （GSC） based speech enhancement, a leakage constraints decision feedback generalized sidelobe canceller（LCDF-GSC） algorithm is proposed. The method adopts DF-GSC against signal mismatch, and introduces a leakage factor in the cost function to deal with the speech leakage problem which is caused by the part of the speech signal in the noise reference signal. Simulation results show that although the signal-to-noise ratio （SNR） of the speech signal through LCDF-GSC is slightly less than that of DF-GSC, the IS measurements show that the distortion of the former is less than that of the latter. MOS （mean opinion score） scores also indicate that the LCDF-GSC algorithm is better than DF- GSC and the Weiner filter algorithm,展开更多
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 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
文摘根据社会语言学理论,男性和女性的说话倾向性往往不同,其中增强语因与女性说话者联系在一起。本文旨在通过将美国电视连续剧“How I Met Your Mother”中的台词为语料,探索所选增强语在使用中的性别差异,包括在增强语选择和增强语搭配方面的性别差异。由于副词增强语的比例较大,因此本文主要关注副词放大器的使用。
文摘"Brevity is the soul of wit". 人们一向主张可以简洁为贵。然而“反复”(repetition)用之得当,则具有强调(emphasis)、鲜明突出(lucidity)等修辞功能,同时还富有韻律(rhythm)美。人们常用之以增强语势、烘托气氛,使重点更突出、使典型形象更鲜明;也常用之以增添感染力、增强鼓动性,使强烈的感情更炽热、使消极的心绪更低沉,对此,笔者曾写过“【反复】在文学作品中的运用,一英语修辞文体谈”,着重讨论其修辞功能,本文试图对修辞性“反复”的诸多构成形式进行分类归纳,供修辞学者参考。
文摘针对5G网络优化工作中出现的新空口承载语音(Voice over New Radio,VoNR)用户感知差的问题,探讨平均意见评分(Mean Opinion Score,MOS)值影响因素与分析流程,对后续出现的此类问题提供分析思路及具体解决方案。通过对网络现有参数和物理参数的核查,修改网络异常参数,以射频优化为基础、以参数优化为辅助,达到快速提升5G VoNR语音用户使用感知的目的。通过采用相应的网络优化手段,有效提升5G网络VoNR接通率,降低5G网络VoNR掉话率。
基金The National Natural Science Foundation of China(No60472058)the Ph.D.Programs Foundation of Ministry of Educa-tion of China(No20050286001)Program for New Century Excellent Talents in University(NoNCET-04-0483)
文摘In order to improve the performance of general sidelobe canceller （GSC） based speech enhancement, a leakage constraints decision feedback generalized sidelobe canceller（LCDF-GSC） algorithm is proposed. The method adopts DF-GSC against signal mismatch, and introduces a leakage factor in the cost function to deal with the speech leakage problem which is caused by the part of the speech signal in the noise reference signal. Simulation results show that although the signal-to-noise ratio （SNR） of the speech signal through LCDF-GSC is slightly less than that of DF-GSC, the IS measurements show that the distortion of the former is less than that of the latter. MOS （mean opinion score） scores also indicate that the LCDF-GSC algorithm is better than DF- GSC and the Weiner filter algorithm,
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.
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.
