面向语音情感识别的语谱特征提取算法研究

语音情感识别的精度很大程度上取决于不同情感间的特征差异性。从分析语音的时频特性入手,结合人类的听觉选择性注意机制,提出一种基于语谱特征的语音情感识别算法。算法首先模拟人耳的听觉选择性注意机制,对情感语谱信号进行时域和频域上的分割提取,从而形成语音情感显著图。然后,基于显著图,提出采用Hu不变矩特征、纹理特征和部分语谱特征作为情感识别的主要特征。最后,基于支持向量机算法对语音情感进行识别。在语音情感数据库上的识别实验显示,提出的算法具有较高的语音情感识别率和鲁棒性,尤其对于实用的烦躁情感的识别最为明显。此外,不同情感特征间的主向量分析显示,所选情感特征间的差异性大,实用性强。     

实用语音情感识别中的若干关键技术

本文介绍了语音情感识别领域的最新进展和今后的发展方向,特别是介绍了结合实际应用的实用语音情感识别的研究状况。主要内容包括：对情感计算研究领域的历史进行了回顾,探讨了情感计算的实际应用;对语音情感识别的一般方法进行了总结,包括情感建模、情感数据库的建立、情感特征的提取,以及情感识别算法等;结合具体应用领域的需求,对实用语音情感识别方法进行了重点分析和探讨;分析了实用语音情感识别中面临的困难,针对烦躁等实用情感,总结了实用情感语音语料库的建立、特征分析和实用语音情感建模的方法等。最后,对实用语音情感识别研究的未来发展方向进行了展望,分析了今后可能面临的问题和解决的途径。     

基于情感特征分类的语音情感识别研究

针对语音信号的实时性和不确定性,提出证据信任度信息熵和动态先验权重的方法,对传统D-S证据理论的基本概率分配函数进行改进;针对情感特征在语音情感识别中对不同的情感状态具有不同的识别效果,提出对语音情感特征进行分类。利用各类情感特征的识别结果,应用改进的D-S证据理论进行决策级数据融合,实现基于多类情感特征的语音情感识别,以达到细粒度的语音情感识别。最后通过算例验证了改进算法的迅速收敛和抗干扰性,对比实验结果证明了分类情感特征语音情感识别方法的有效性和稳定性。     

语音情感识别综述

人类的语音情感变化是一个抽象的动态过程,难以使用静态信息对其情感交互进行描述,而人工智能的兴起为语音情感识别的发展带来了新的契机。从语音情感识别的概念和在国内外发展的历史进程入手,分别从5个方面对近些年关于语音情感识别的研究成果进行了归纳总结。介绍了语音情感特征,归纳总结了各种语音特征参数对语音情感识别的意义。分别对语音情感数据库的分类及特点、语音情感识别算法的分类及优缺点、语音情感识别的应用以及语音情感识别现阶段所遇到的挑战进行了详细的阐述。立足于研究现状对语音情感识别的未来研究及其发展进行了展望。     

基于蚁群算法特征选择的语音情感识别

情感特征提取是语音情感准确识别的关键,传统方法采用单一特征或者简单组合特征提取方法,单一特征无法全面反映语音情感变化,简单组合特征会使特征间产生大量冗余特征,影响识别正确结果.为了提高语音情感识别率,提了一种蚁群算法的语音情感智能识别方法.首先采用语音识别正确率和特征子集维数加权作为目标函数,然后利用蚁群算法找到最优语音特征子集,消除特征冗余信息.通过汉话和丹麦语两种情感语音库进行仿真测试,仿真结果表明,改进方法不仅消除了冗余、无用特征,降低了特征维数,而且提高了语音情感识别率,是一种有效的语音情感智能识别方法.     

融合语音情感词局部特征的语音情感识别方法

为有效利用语音情感词局部特征,提出了一种融合情感词局部特征与语音语句全局特征的语音情感识别方法。该方法依赖于语音情感词典的声学特征库,提取出语音语句中是否包含情感词及情感词密度等局部特征,并与全局声学特征进行融合,再通过机器学习算法建模和识别语音情感。对比实验结果表明,融合语音情感词局部特征与全局特征的语音情感识别方法能取得更好的效果,局部特征的引入能有效提高语音情感识别准确率。     

基于关联规则的语音情感中韵律特征抽取算法研究

近年来,情感计算一直是学术界研究的热点问题。语音情感识别作为情感计算的重要研究且涉及到人工智能、模式识别、机器学习等多个领域。针对语音情感识别中特征挖掘的复杂性,利用关联规则挖掘算法对语音特征中的韵律特征与所包含情感之间的关联关系进行研究。主要进行如下工作:(1)针对语音情感的特点,给出了情感频繁项集的概念;(2)提出基于关联规则的语音情感中韵律特征抽取算法(PFEA_AR);(3)在汉语情感数据集上进行相关实验,取得了85%的识别率,比fisher准则判别法的精度提高了10%。实验结果表明,通过关联规则算法所抽取的特征在降低维度的同时还能够有效提高情感分类精度,从而验证了新算法所抽取特征的有效性。     

语音情感识别研究进展综述

对语音情感识别的研究现状和进展进行了归纳和总结,对未来语音情感识别技术发展趋势进行了展望. 从5个角度逐步展开进行归纳总结,即情感描述模型、具有代表性的情感语音库、语音情感特征提取、语音情感识别算法研究和语音情感识别技术应用,旨在尽可能全面地对语音情感识别技术进行细致的介绍与分析,为相关研究人员提供有价值的学术参考;最后,立足于研究现状的分析与把握,对当前语音情感识别领域所面临的挑战与发展趋势进行了展望.侧重于对语音情感识别研究的主流方法和前沿进展进行概括、比较和分析.     

基于SVM的语音情感识别算法

为有效提高语音情感识别系统的识别正确率,提出一种基于SVM的语音情感识别算法.该算法提取语音信号的能量、基音频率及共振峰等参数作为情感特征,采用SVM(Support Vector Machine,支持向量机)方法对情感信号进行建模与识别.在仿真环境下的情感识别实验中,所提算法相比较人工神经网络的ACON(All Cl...     

语音情感识别中特征参数的研究进展

语音情感识别是近年来新兴的研究课题之一,特征参数的提取直接影响到最终的识别效率,特征降维可以提取出最能区分不同情感的特征参数。提出了特征参数在语音情感识别中的重要性,介绍了语音情感识别系统的基本组成,重点对特征参数的研究现状进行了综述,阐述了目前应用于情感识别的特征降维常用方法,并对其进行了分析比较。展望了语音情感识别的可能发展趋势。     

构建安全的局域网策略

网络安全是一门涉及计算机科学、网络技术、密码技术、信息安全技术、应用数学、教论、信论等多种学科的综合性学科,它涉及的因素主要包括物理安全、系统安全、信息安全和文化安全等范围。局域网络中人为的、非人为的,有意的、无意的;非法用户入侵、计算机病毒、黑客的不断侵袭等随时威胁局域网的安全。随着计算机网络技术迅速发展,网络安全问题也日渐突出。该文分析了威胁局域网安全的主要因素,探讨了从物理环境、网络层、应用层以及管理制度方面,运用VPN、NAT、VLAN、IDS、身份验证等技术构建安全局域网的策略。     

Teaching mineral prospecting by computer-assisted simulation techniques

The simulation game, which involves the interaction of a geological model, a set of rules, and teaching materials, is used to teach students and professional people attending refresher courses the techniques of mineral exploration. Using geochemical and geophysical measurements, including detailed borehole logs, the students plan an exploration strategy, control the exploration budget, discover the structure and geology of the area represented by the model, outline probable mineralizations, and evaluate the ore reserves. They choose the borehole locations, the type of drilling machine, and the drilling depth, taking continually into consideration the financial aspects.The model is multidisciplinary, involving stratigraphy, sedimentology, structural geology, tectonics, climatic conditions, metallogeny, mineralogy, and petrology. Certain of these characteristics are expressed as complex mathematical functions, which are solved by the program. The computer program also prints out the detailed borehole logs, controls the budget and drilling equipment, and enforces the rules of the game.     

基于木马的黑客攻击技术

木马程序一般分为客户端程序和服务端程序两部分,客户端程序用于远程控制计算机。而服务端程序,则隐藏到远程计算机中,接收并执行客户端程序发出的命令。本文首先介绍了木马的定义,功能和特点,其次介绍了木马的常见植入技术,包括网站挂马,发送超级链接,电子邮件,缓冲区溢出,和其它病毒形态相结合五种。再次阐述了木马的自启动技术,然后是木马的隐藏技术,包括文件隐藏,进程隐藏和通信隐藏。最后是木马的免杀技术,主要包括加壳,修改特征码和加花指令。     

The Design and Role of Synthetic Creative Traits in Artificial Ant Colonies

Previous and current research on ant colonies have focused on the emergence of complex and sophisticated group-behaviors that are characteristic of the whole colony, starting from simple rules characterizing each individual ant. Examples of emergent behaviors include foraging and nest building. While social scientists, biologists, and physicists have focused on observing and analyzing the behavior of actual ants, researchers in computer science have investigated through modeling and simulation of synthetic ants on the computer, the emergent behavior in a collection of simple robots, simulated evolution of computer programs, and the formation of pheromone patterns during foraging under unlimited food supply. This paper has two objectives. First, it presents a systematic study, through behavior modeling and simulation, of the influence of the presence or absence of pheromone, the duration interval of pheromone, the extent of the food supply at the food sources, the size of the colony, and the search strategy employed during foraging, for a given geometry and a finite number of food sources, on the performance of the ant colony. The second and most important objective of this paper is to scientifically study the nature of creativity by modeling synthetic creativity in an ant colony, simulating it on a computer system, and measuring its impact on performance through innovative metric design. The study is motivated by leading thinkers, throughout time, who have strongly emphasized the importance of creativity over intelligence. While an exact and universal definition of creativity is elusive, the important characteristics include originality, intuition, and imagination. Creativity is best understood through its manifestations as novel and radically different ideas that transcend current knowledge and reasoning. In this study, two synthetic creativity traits are introduced into select individual ants of a colony by imparting to them a foraging behavior that is radically different from the normal behavior. Under the first trait, the creative ants choose to ignore the existing pheromone trails and search for food sources. Under the second trait, a creative ant shares its knowledge of food source location, after discovery, with all other creative ants, so that together they can focus solely on discovering new food sources. Analysis of the simulation results reveal that a creative trait coupled with the underlying parameters of the ant colony may cause the foraging completion time metric, i.e. the time to collect food from all sources, to be marginally better or weaker than the normal colony. Contrary to intuition, the completion time metric worsens when, in a fixed sized colony, the number of creative ants, relative to normal ants, becomes excessive. Furthermore, for a given finite geometry, finite food supply, and a fixed ratio of the number of creative to normal ants, the impact of creativity on the foraging performance is dependent on the underlying parameters, and may either continue to improve, remain unchanged, or decrease, as the size of the colony increases. Finally, while the creative ants expend, on an average, two to three times more energy than the normal ants, the ant colony with the creative ants discovers more food sources, in less time and, under certain circumstances, a creative colony discovers all food sources which a normal colony can never achieve.     

社交网络技术在科研教学环境中的应用研究

随着互联网产业的发展、用户规模的扩张和用户行为的变化,以Web2.0为特征的相关需求应运而生。SNS,Social Networking Services,专指旨在帮助人们建立社会性网络的互联网应用服务。依赖其开放性,即时性,互动性,不受时间地点约束等特点获得青睐,很多社交网站如twitter,Facebook,人人网,微博在流量、用户数和市值都有引人瞩目的成绩。社交网络的特性适用于知识的共享,将SNS和E-learning结合产生的面向知识管理的社交网络KMOS系统既使学生在社交网络服务中获取到知识,又打破传统教学受时间、地点的束缚,开放共享知识,一对多的高效传播模式。设计和实现的面向知识管理的社交网络服务拥有的上述优点。使用列表和群组控制多媒体资源的传播范围。分层和插件式设计使系统灵活应对需求改变。使用社交网络技术提高教学质量。     

客户思维在工业设计中的应用

工业设计中的客户思维分为三个类别:对外部客户的客户思维,对合作伙伴(合作部门)的客户思维,对内部同事的客户思维。对外部的客户要为客户、替客户思考,逆向思维,管理客户行为——进行规范化管理,引导客户思维。对合作伙伴(合作部门)的客户,要采取合作的态度、运用共赢思维,把合作者当客户——不苛求、不退让、不推脱,分工协作,引导整体走向。对内部同事应用客户思维,其实就是营造一种尊重、体谅、共赢、和谐、温暖的内部文化氛围,带动整体工作的提升。     

多特征融合的lncRNA识别与其功能预测

针对传统的基于单一特征的植物lncRNA识别的局限性,提出了融合RNA序列的开放阅读框、二级结构以及k-mers等多特征方法,训练高斯朴素贝叶斯、支持向量机和梯度提升决策树3种经典的分类模型,并实现分类结果的集成,利用交叉验证对模型的性能进行了评估,整体性能优于目前较流行的CPAT、CNCI和PLEK预测软件,在拟南芥数据集上总体的准确率达到了89%。另外,基于内源性竞争规则以及RNA结构信息,分别对lncRNA-microRNA和microRNA-mRNA进行靶向预测、筛选,再通过整合预测数据建立互作网络,并对网络模块中的lncRNA进行功能预测。通过GO术语分析,对与mRNA相关的lncRNA可能参与的生物调控过程进行预测,推测它们的相应功能。     

Design and analysis of the Dual-Torus Network

In this paper, we propose a new topology called theDual Torus Network (DTN) which is constructed by adding interleaved edges to a torus. The DTN has many advantages over meshes and tori such as better extendibility, smaller diameter, higher bisection width, and robust link connectivity. The most important property of the DTN is that it can be partitioned into sub-tori of different sizes. This is not possible for mesh and torus-based systems. The DTN is investigated with respect to allocation, embedding, and fault-tolerant embedding. It is shown that the sub-torus allocation problem in the DTN reduces to the sub-mesh allocation problem in the torus. With respect to embedding, it is shown that a topology that can be embedded into a mesh with dilation δ can also be embedded into the DTN with less dilation. In fault-tolerant embedding, a fault-tolerant embedding method based on rotation, column insertion, and column skip is proposed. This method can embed any rectangular grid into its optimal square DTN when the number of faulty nodes is fewer than the number of unused nodes. In conclusion, the DTN is a scalable topology well-suited for massively parallel computation. Sang-Ho Chae, M.S.: He received the B.S. in the Computer Science and Engineering from the Pohang University of Science and Technology (POSTECH) in 1994, and the M.E. in 1996. Since 1996, he works as an Associate Research Engineer in the Central R&D Center of the SK Telecom Co. Ltd. He took part in developing SK Telecom Short Message Server whose subscribers are now over 3.5 million and Advanced Paging System in which he designed and implemented high availability concepts. His research interests are the Fault Tolerance, Parallel Processing, and Parallel Topolgies. Jong Kim, Ph.D.: He received the B.S. degree in Electronic Engineering from Hanyang University, Seoul, Korea, in 1981, the M.S. degree in Computer Science from the Korea Advanced Institute of Science and Technology, Seoul, Korea, in 1983, and the Ph.D. degree in Computer Engineering from Pennsylvania State University, U.S.A., in 1991. He is currently an Associate Professor in the Department of Computer Science and Engineering, Pohang University of Science and Technology, Pohang, Korea. Prior to this appointment, he was a research fellow in the Real-Time Computing Laboratory of the Department of Electrical Engineering and Computer Science at the University of Michigan from 1991 to 1992. From 1983 to 1986, he was a System Engineer in the Korea Securities Computer Corporation, Seoul, Korea. His major areas of interest are Fault-Tolerant Computing, Performance Evaluation, and Parallel and Distributed Computing. Sung Je Hong, Ph.D.: He received the B.S. degree in Electronics Engineering from Seoul National University, Korea, in 1973, the M.S. degree in Computer Science from Iowa State University, Ames, U.S.A., in 1979, and the Ph.D. degree in Computer Science from the University of Illinois, Urbana, U.S.A., in 1983. He is currently a Professor in the Department of Computer Science and Engineering, Pohang University of Science and Technology, Pohang, Korea. From 1983 to 1989, he was a staff member of Corporate Research and Development, General Electric Company, Schenectady, NY, U.S.A. From 1975 to 1976, he was with Oriental Computer Engineering, Korea, as a Logic Design Engineer. His current research interest includes VLSI Design, CAD Algorithms, Testing, and Parallel Processing. Sunggu Lee, Ph.D.: He received the B.S.E.E. degree with highest distinction from the University of Kansas, Lawrence, in 1985 and the M.S.E. and Ph.D. degrees from the University of Michigan, Ann Arbor, in 1987 and 1990, respectively. He is currently an Associate Professor in the Department of Electronic and Electrical Engineering at the Pohang University of Science and Technology (POSTECH), Pohang, Korea. Prior to this appointment, he was an Associate Professor in the Department of Electrical Engineering at the University of Delaware in Newark, Delaware, U.S.A. From June 1997 to July 1998, he spent one year as a Visiting Scientist at the IBM T. J. Watson Research Center. His research interests are in Parallel, Distributed, and Fault-Tolerant Computing. Currently, his main research focus is on the high-level and low-level aspects of Inter-Processor Communications for Parallel Computers.     

BERT-TECNN模型的文本分类方法研究

由于Bert-base,Chinese预训练模型参数巨大,在做分类任务微调时内部参数变化较小,易产生过拟合现象,泛化能力弱,且该模型是以字为单位进行的预训练,包含词信息量较少。针对这些问题,提出了BERT-TECNN模型,模型使用Bert-base,Chinese模型作为动态字向量模型,输出包含深度特征信息的字向量,Transformer encoder层再次对数据进行多头自注意力计算,提取特征信息,以提高模型的泛化能力,CNN层利用不同大小卷积核,捕捉每条数据中不同长度词的信息,最后应用softmax进行分类。该模型与Word2Vec+CNN、Word2Vec+BiLSTM、Elmo+CNN、BERT+CNN、BERT+BiLSTM、BERT+Transformer等深度学习文本分类模型在三种数据集上进行对比实验,得到的准确率、精确率、召回率、F1测度值均为最高。实验表明该模型有效地提取了文本中字词的特征信息,优化了过拟合问题,提高了泛化能力。     

协作机器人的构型分析研究

针对协作机器人的构型分析研究,得出了偏置是影响机器人构型的一个重要因素。首先,对现有典型协作机器人的构型进行分析,通过构型间的内在联系与演化过程得到构型之间的差异。然后利用构型之间的差异引出了偏置的定义,并通过偏置对关节运动范围的影响将其分为S型偏置和Y型偏置。最后以全局性能指标、工作空间体积指标和灵活工作空间指标为性能评价标准,对iiwa、Sawyer、Yumi三种典型构型的性能进行了仿真。通过对比分析可知,偏置的存在使构型的全局性能和工作空间体积性能降低,但对灵活工作空间性能有提高作用。结果表明偏置是影响机器人性能的重要因素,该分析研究为协作机器人的构型设计提供了理论依据。