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AN OPTIMAL INFORMATION HIDING ALGORITHM FOR SPEECH IN THE FRACTIONAL FOURIER TRANSFORM DOMAIN

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Journal of Electronics(China) 2010年第4期27卷 564-570页

作者： Xi Ji zou cairong Bao Yongqiang Wang Qingyun School of Information Science and Engineering Southeast University Nanjing 210096 China College of Computer and Information Hohai University Changzhou 213022 China School of Communication Engineering Nanjing Institute of Technology Nanjing 21116 China

With the increasing requirement of military and security, the technology of information hiding for speech becomes a hotspot and difficulty in the fields of speech signal processing and in-formation security, which is developing rapidly. In order to stand against the stegano-analysis, the paper proposed an optimal information hiding algorithm for speech in the Fractional Fourier Transform (FrFT) domain based on the Minimum Mean Square Error (MMSE) criterion. The results of simulation and experiments show that speech modified by the proposed algorithm has no remarkable changes both in time and frequency domains, which can effectively resist the time and frequency analysis, Otherwise, the algorithm is robust to general signal process attack, and the difference is imperceptible between the original and modified speech.

关键词： Practional Fourier Transform (FrFT) Speech information hiding Minimum Mean Square Error (MMSE)

OPTIMIZED SUB-BAND ADAPTIVE AEC USING EAR AUDITORY FEATURE

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Journal of Electronics(China) 2007年第2期24卷 267-270页

作者： Qiao Jie Zhao Li zou cairong Department of Radio Engineering Southeast University Nanjing 210096 China

Acoustic echo cancellation based on sub-band filters has the characteristics of rapid con- vergence and small computational complexity. This letter analyses two different sub-band filters design methods which used in acoustic echo cancellation fields and compares them with each other. Fur- thermore, the sub-band filter construction have been optimized, which lead to the improvement of the computational efficiency. At the same time, this letter combines ear auditory feature with acoustic echo cancellation, thus improves the original algorithms by importing a new objective function creatively. At the last part, a simulation environment has been designed and a computer simulation has been carried out. The final results indicate that this method can meet the requirements of actual projects, and some improvements are demonstrated on performance and calculation quantity compared to original algo- rithms.

关键词： AEC (Acoustic Echo Cancellation) Adaptive filter Auditory feature

SPEECH EMOTION RECOGNITION USING MODIFIED QUADRATIC DISCRIMINATION FUNCTION

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Journal of Electronics(China) 2008年第6期25卷 840-844页

作者： Zhao Yan Zhao Li zou cairong Yu Yinhua School of Information Science and Technology Southeast University Nanjing 210096 China

Quadratic Discrimination Function （QDF） is commonly used in speech emotion recognition, which proceeds on the premise that the input data is normal distribution. In this paper, we propose a transformation to normalize the emotional features, emotion recognition. Features based on prosody then derivate a Modified QDF （MQDF） to speech and voice quality are extracted and Principal Component Analysis Neural Network （PCANN） is used to reduce dimension of the feature vectors. The results show that voice quality features are effective supplement for recognition, and the method in this paper could improve the recognition ratio effectively.

关键词： Speech emotion recognition Principal Component Analysis Neural Network (PCANN) Modified Quadratic Discrimination Function (MQDF)

Research on Nonlinear Frequency Compression Method of Hearing Aid with Adaptive Compression Ratio

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Computer Modeling in Engineering & Sciences 2019年第11期121卷 551-567页

作者： Xia Wang Hongming Shen Huawei Tao Ruiyu Liang Xing Deng Haijian Shao Li Zhao cairong zou School of Information Science and Technology Nantong UniversityNantong226019China School of Information Science and Engineering Henan University of TechnologyZhengzhou450001China School of Communication Engineering Nanjing Institute of TechnologyNanjing211167China School of Automation Key Laboratory of Measurement and Control for CSEMinistry of EducationSoutheast UniversityNanjing210096China School of Computer Science Jiangsu University of Science and TechnologyZhenjiang212003China School of Information Science and Engineering Southeast UniversityNanjing210096China

To make full use of the residual audible frequency band of hearing-loss patients and improve the intelligibility of speech,an adaptive nonlinear frequency compression(NFC)algorithm is proposed,which amplifies signals below the cutoff frequency while compresses signals above the cutoff ***,high-frequency signals are decomposed to critical band signals according to the BARK ***,the global compression ratio is determined according to the patient's cutoff frequency and maximum audible ***,the sub-band compression ratio is adaptively determined based on the global compression ratio and normalized average energy of subband ***,the high frequency signals are transposed to low frequency bands by compression mapping,and the phases are adjusted to the same as the original low frequency *** results of speech intelligibility with nine subjects demonstrate that compared to conventional amplitude amplification and nonlinear frequency compression algorithms the proposed algorithm significantly improves the intelligibility of initials and sentences,while not affects the intelligibility of finals and tones significantly.

关键词： Frequency compression sensorineural hearing loss hearing aids

Speech emotion recognition based on statistical pitch model

维普期刊数据库评论

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Chinese Journal of Acoustics 2006年第1期25卷 87-96页

作者： WANG Zhiping ZHAO Li zou cairong Department of Radio Engineering Southeast University Nanjing 210096

A modified Parzen-window method, which keep high resolution in low frequencies and keep smoothness in high frequencies, is proposed to obtain statistical model. Then, a gender classification method utilizing the statistical model is proposed, which have a 98% accuracy of gender classification while long sentence is dealt with. By separation the male voice and female voice, the mean and standard deviation of speech training samples with different emotion are used to create the corresponding emotion models. Then the Bhattacharyya distance between the test sample and statistical models of pitch, are utilized for emotion recognition in speech. The normalization of pitch for the male voice and female voice are also considered, in order to illustrate them into a uniform space. Finally, the speech emotion recognition experiment based on K Nearest Neighbor shows that, the correct rate of 81% is achieved, where it is only 73.85% if the traditional parameters are utilized.

关键词： emotion recognition statistical models classification method standard deviation high frequencies low frequencies high resolution uniform space test sample

Recognition of practical speech emotion using improved shuffled frog leaping algorithm

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Chinese Journal of Acoustics 2014年第4期33卷 441-456页

作者： ZHANG Xiaodan HUANG Chengwei ZHAO Li zou cairong Key Laboratory of Underwater Acoustic Signal Processing of Ministry of Education Southeast University

Due to the drawbacks in Support Vector Machine（SVM）parameter optimization,an Improved Shuffled Frog Leaping Algorithm（Im-SFLA）was proposed,and the learning ability in practical speech emotion recognition was ***,we introduced Simulated Annealing（SA）,Immune Vaccination（Iv）,Gaussian mutation and chaotic disturbance into the basic SFLA,which bManced the search efficiency and population diversity ***,Im-SFLA Was applied to the optimization of SVM parameters,and an Im-SFLA-SVM method Was ***,the acoustic features of practical speech emotion,such aS ridgetiness,were *** pitch frequency,short-term energy,formant frequency and chaotic characteristics were analyzed corresponding to different emotion categories,and we constructed a 144-dimensional emotion feature vector for recognition and reduced to 4-dimension by adopting Linear Discriminant Analysis（LDA） Finally,the Im-SFLA-SVM method Was tested on the practical speech emotion database,and the recognition results were compared with Shuffled Frog Leaping Algorithm optimization-SVM（SFLA-SVM）method,Particle Swarm Optimization algorithm optimization-SVM（PSo-SVM） method,basic SVM,Gaussian Mixture Model（GMM）method and Back Propagation（BP）neural network *** experimentM resuits showed that the average recognition rate of Im-SFLA-SVM method was 77.8%,which had improved 1.7%,2.7%,3.4%,4.7%and 7.8%respectively,compared with the other *** recognition of fidgetiness was significantly improve,thus verifying that Im-SFLA was an effective SVM parameter selection method,and the Im-SFLA-SVM method may significantly improve the practical speech emotion recognition.

关键词： SFLA SVM Recognition of practical speech emotion using improved shuffled frog leaping algorithm

采用归一化补偿变换的与文本无关的说话人识别

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声学学报 2006年第1期31卷 55-60页

作者：包永强赵力邹采荣东南大学无线电工程系南京210096

在噪声环境下,特别是当说话人识别最常用的模型——高斯混合模型(GMM)失配的情况下,需要对其输出帧似然概率的统计特性进行补偿。文章根据说话人识别的声学特性,提出了一种非线性变换方法——归一化补偿变换。理论分析和实验结果表明:... 详细信息

在噪声环境下,特别是当说话人识别最常用的模型——高斯混合模型(GMM)失配的情况下,需要对其输出帧似然概率的统计特性进行补偿。文章根据说话人识别的声学特性,提出了一种非线性变换方法——归一化补偿变换。理论分析和实验结果表明:与常用的最大似然(ML)变换相比,该变换能够提高系统识别率,最大可达3．7％,同时可降低误识率,最大可达45．1％。结果说明归一化补偿变换方法基本克服了在与文本无关说话人识别系统中,当说话人的个性特征不断变化、语音与噪声不能很好地分离或者降噪算法对语音有损伤、模型不能很好地匹配时,需要对模型输出的似然概率(得分)进行补偿的局限。这也说明对模型输出的似然概率进行处理是降低噪声和干扰的影响、提高说话人识别率的有效方法。

关键词：说话人识别系统与文本无关高斯混合模型(GMM) 归一化补偿噪声环境变换方法统计特性声学特性最大似然

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时延服务质量约束下的高能效功率分配算法

东南大学学报（自然科学版） 2015年第4期45卷 635-640页

作者：左加阔赵力邹采荣东南大学教育部水声信号处理重点实验室南京210096

为了在保障系统Qo S的同时提高系统的能量效率,以有效容量与功耗的比值作为优化目标,研究了时延Qo S约束下认知OFDMA系统中的高能效功率分配问题.为了保护主用户传输不受次用户传输的影响,对次用户的发射功率和次用户对主用户的干扰进... 详细信息

为了在保障系统Qo S的同时提高系统的能量效率,以有效容量与功耗的比值作为优化目标,研究了时延Qo S约束下认知OFDMA系统中的高能效功率分配问题.为了保护主用户传输不受次用户传输的影响,对次用户的发射功率和次用户对主用户的干扰进行了约束.由于原优化问题为非线性分式规划问题,很难对其进行直接求解.为便于求解,首先通过引入变量将原优化问题转化为易于处理的一维优化问题和传统的有效容量最大化问题,然后采用黄金分割法对上述等效问题进行求解,最后提出了一种迭代的高能效功率分配算法.实验结果表明,与传统的有效容量最大化算法相比,提出的算法能够有效地提高系统的能量效率.

关键词：认知无线电功率分配能量效率有效容量

基于基音参数规整及统计分布模型距离的语音情感识别

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声学学报 2006年第1期31卷 28-34页

作者：王治平赵力邹采荣东南大学无线电工程系南京210096

提出一种根据基音提取的频率分辨率确定自适应窗口的改进Parzen窗方法估计基音概率密度,兼顾了基音统计分布模型在低频段的高分辨率和高频段的平滑;提出利用不同性别的基音分布规律的性别区分算法,对于长句可以达到98%的识别率;通过分... 详细信息

提出一种根据基音提取的频率分辨率确定自适应窗口的改进Parzen窗方法估计基音概率密度,兼顾了基音统计分布模型在低频段的高分辨率和高频段的平滑;提出利用不同性别的基音分布规律的性别区分算法,对于长句可以达到98%的识别率;通过分析基音均值、方差、统计分布模型在性别上的差异,对基音参数进行基于性别差异的规整;引入规整后的基音均值和基音方差,以及基音统计分布模型距离作为情感特征参数;最后利用K最近邻方法对汉语情感语料进行识别。利用常规方法提取的参数最后得到的识别率为73．8％,而使用经过性别差异规整的基音参数和基音统计分布距离的识别率提高到 81％。

关键词：基音提取统计分布情感识别分布模型距离自适应窗口语音频率分辨率识别率概率密度