基于得分域多维特征分类器的声纹密码系统

针对不同类型数据对目标发音人区分能力不同的现象,在传统系统基础上提出利用UBM模型对测试数据进行分类,使用分类后的似然比得分形成多维特征,在此基础上利用SVM分类器进行声纹密码确认。该方法把传统的似然比检验策略转换成多维特征空间上的二类分类问题。测试与注册数据同信道情况时,在4种手机数据集上,文中系统相对文本相关GMM-UBM声纹密码系统等错误率分别下降41。25%、33。33%、37。49%和26。03%,在交叉信道上系统性能也获得改善。     

On the study of replay and voice conversion attacks to text-dependent speaker verification

Automatic speaker verification (ASV) is to automatically accept or reject a claimed identity based on a speech sample. Recently, individual studies have confirmed the vulnerability of state-of-the-art text-independent ASV systems under replay, speech synthesis and voice conversion attacks on various databases. However, the behaviours of text-dependent ASV systems have not been systematically assessed in the face of various spoofing attacks. In this work, we first conduct a systematic analysis of text-dependent ASV systems to replay and voice conversion attacks using the same protocol and database, in particular the RSR2015 database which represents mobile device quality speech. We then analyse the interplay of voice conversion and speaker verification by linking the voice conversion objective evaluation measures with the speaker verification error rates to take a look at the vulnerabilities from the perspective of voice conversion.     

Articulatory movement features for short-duration text-dependent speaker verification

During our pronunciation process, the position and movement properties of articulators such as tongue, jaw, lips, etc are mainly captured by the articulatory movement features (AMFs). This paper investigates to use the AMFs for short-duration text-dependent speaker verification. The AMFs can characterize the relative motion trajectory of articulators of individual speakers directly, which is rarely affected by the external environment. Therefore, we expect that, the AMFs are superior to the traditional acoustic features, such as mel-frequency cepstral coefficients (MFCC), to characterize the speaker identity differences between speakers. The speaker similarity scores measured by the dynamic time warping (DTW) algorithm are used to make the speaker verification decisions. Experimental results show that the AMFs can bring significant performance gains over the traditional MFCC features for short-duration text-dependent speaker verification task.     

基于HMM-UBM和短语音的说话人身份确认

提出了一种简单有效的与说话人有关的阈值设置方法 ,同时在确认系统中采用高斯混合模型(GMM)作为背景模型来模拟未知的冒认者的语音 ,在冒认文本多样化的情况下获得了比用隐马尔可夫模型(HMM)作背景模型更好的性能 .本文在此基础上实现了一个基于Internet的与文本有关的远程语音身份认证系统 ,在实验测试和应用测试中均获得了满意的确认性能 .     

区分性训练在声纹密码中的新应用

在声纹密码任务中由于数据稀疏的问题难以实现区分性训练,本文以一种表征距离度量的特征矢量为基础提出新的声纹密码区分性系统框架,对正反例样本的新特征矢量实现了基于最小分类错误准则的区分性训练,将声纹密码从确认问题转化为二类分类问题。在自由说话风格的60人数据集上,声纹密码区分性系统与混合高斯模型-通用背景模型(Gaussian mixture model-universal background model,GMM-UBM)系统融合后等错误率为4.48%,相对GMM-UBM,动态时间规划(Dynamic time warping,DTW)基线系统性能分别提升了17.95%和59.68%。     

基于FPGA的7-Zip加密文档高能效口令恢复方法

随着7-Zip压缩软件的广范使用,破解7-Zip加密文档的口令对信息安全有着非常重要的意义。目前,破解7-Zip加密文档主要采用CPU和GPU平台,而潜在的口令空间大,计算复杂度高,在有限的时间内找到正确的口令需要更高性能的计算平台。因此,文中通过分析解密算法的PMC特性,采用可重构的FPGA硬件计算平台,使用流水线技术来实现数据拼接和SHA-256算法,并利用预计算和CSA方法优化SHA-256算法的关键路径,同时使用双端口RAM存储校验数据,从而满足算法的计算需求和存储需求,实现高效能的7-Zip解密算法。实验数据表明,文中提出的优化方法能大幅提升SHA-256算法的性能,使其吞吐量达到110.080 Gbps,并且通过多种方法对解密算法进行优化,最终破解10位长度口令的速率达到了10608个/s,是CPU的226倍,GPU的1.4倍,且能效比是GPU的8倍,极大地提升了算法的性能,降低了高功耗需求。     

采用GPU的ZIP密码恢复算法

常用的zip密码恢复软件使用通用处理器进行密码恢复,每秒尝试密码次数少,往往需要很长时间才能找到正确密码。为了提高密码破解效率,提出了GPU平台上的快速ZIP密码恢复算法,针对GPU的特点,重点优化了寄存器使用以及存储器访问,对AES和HMAC算法进行了并行优化,充分发挥了GPU大规模并行运算的优势,并利用ZIP文档格式中的密码校验位提前筛选密码,大部分错误密码都不需要进行后续运算。实验结果表明,恢复AES-128加密的ZIP文档,基于GPU的算法实现了11.09倍的加速比。     

普通话水平测试电子化系统

普通话水平测试电子化系统有助于高效地进行普通话水平测试。本文在100小时标准发音人数据库的基础上,针对汉语发音特点,利用语言学专家知识,引入语料选择的自适应算法改进了传统的语音评测算法。在500人普通话水平测试数据库上的测试结果表明,新评测算法能有效提升评测性能。经过分段线性映射,机器评分和人工评分的误差(2.44)和人工与人工评分之间的误差(2.30)相当。这表明可以使用机器代替人工进行普通话水平测试的前三项评分工作。     

Evaluation of a vector quantization talker recognition system in text independent and text dependent modes

A vector quantization based talker recognition system is described and evaluated. The system is based on constructing highly efficient short-term spectral representations of individual talkers using vector quantization codebook construction techniques. Although the approach is intrinsically text-independent, the system can be easily extended to text-dependent operation for improved performance and security by encoding specified training word utterances to form word prototypes. The system was evaluated using a 100-talker database of 20 000 digits spoken in isolation. In a talker verification mode, average equal-error rate performance of 2·2% for text-independent operation and 0·3% for text-dependent operation was obtained for 7-digit long test utterances. Because the evaluation database was restricted to the vocabulary of spoken digits, the text-independent operation of the system has not been formally tested beyond the confines of that vocabulary.     

Computer-access security systems using keystroke dynamics

An approach to securing access to computer systems is described. By performing real-time measurements of the time durations between the keystrokes when a password is entered and using pattern-recognition algorithms, three online recognition systems were devised and tested. Two types of passwords were considered: phrases and individual names. A fixed phrase was used in the identification system. Individual names were used as a password in the verification system and in the overall recognition system. All three systems were tested and evaluated. The identification system used 10 volunteers and gave an indecision error of 1.2%. The verification system used 26 volunteers and gave an error of 8.1% in rejecting valid users and an error of 2.8% in accepting invalid users. The overall recognition system used 32 volunteers and gave an error of 3.1% in rejecting valid users and an error of 0.5% in accepting invalid users     

一种基于二次剩余的动态口令算法*

针对基于动态口令的电子商务身份认证机制存在计算和通信负担过重及不能对用户的使用次数和使用时间进行控制的问题,利用二次剩余理论中计算模平方根的复杂性提出一种基于二次剩余的动态口令算法。本算法具有失效次数和失效时间两个特性,因为不需要任何口令和验证表,可以避免重放攻击,因此具有稳定的安全性。这些特点使其适合用于电子商务,如在线游戏、付费电视等。另外本算法客户端计算量很小,可以用于手机等计算能力有限的环境。     

基于基音周期与清浊音信息的梅尔倒谱参数

提出一种在浊音部分不固定帧长的梅尔倒谱参数(Mel-cepstrum)提取的方法。针对浊音和清音所包含信息量不同,对浊音进行双倍的加权,从而将基音与清浊音信息融合进梅尔倒谱参数。将这种动态的梅尔倒谱参数应用在说话人确认中,在混合高斯模型(Gaussian mixture models,GMM)的情况下,取得了比常用的梅尔刻度式倒频谱参数(Mel-frequency cepstral coefficient,MFCC)更高的识别率,在NIST 2002年测试数据库中,512个混合高斯下能够将等错误率(EER)由9.4%降低到8.3%,2 048个混合高斯下能够将等错误率由7.8%降低到6.9%。     

Towards better making a decision in speaker verification

Speaker verification is a process that accepts or rejects the identity claim of a speaker. How to make a decision is a critical problem; a threshold for decision-making critically determines performance of a speaker verification system. Traditional threshold estimation methods take only information conveyed by training data into consideration and, to a great extent, do not relate it to production data. It turns out that a speaker verification system with such threshold estimation suffers from poor performance in reality due to mismatches. In this paper, we propose several methods towards better decision-making in a practical speaker verification system. Our methods include the use of additional reliable statistical information for threshold estimation, elimination of abnormal data for better estimation of underlying statistics, and on-line incremental threshold update. To evaluate the performance of our methods, we have done simulations based on a baseline system, Gaussian Mixture Model, in both text-dependent and text-independent modes. Comparative results show that in contrast to the recent threshold estimation methods our methods yield considerably better performance, especially on miscellaneous mismatch conditions, in terms of generalization. Thus our methods provide a promising way for real speaker verification applications.     

面向分级身份密码批验签的错误签名混合筛选算法

针对分级身份密码（HIBC）批验签过程中的错误签名快速识别问题,设计实现了一种错误签名混合筛选算法。针对HIBC签名算法不完全聚合的特点,首先将所有签名作为树叶构造平衡二叉树,然后通过拆分攻克与指数测试方法查找错误签名,并且利用计算中间值的关联性减少计算开销。算法性能分析表明,当批验签中错误签名数大于2时,该算法计算开销低于独立测试、通用折半拆分、指数测试以及裁剪搜索算法,能够有效筛选出HIBC批验签中的错误签名,可以应用在云计算认证等应用场景中。     

Multi-style speaker recognition database in practical conditions

This work describes the process of collection and organization of a multi-style database for speaker recognition. The multi-style database organization is based on three different categories of speaker recognition: voice-password, text-dependent and text-independent framework. Three Indian institutes collaborated for the collection of the database at respective sites. The database is collected over an online telephone network that is deployed for speech based student attendance system. This enables the collection of data for a longer period from different speakers having session variabilities, which is useful for speaker verification (SV) studies in practical scenario. The database contains data of 923 speakers for the three different modes of SV and hence termed as multi-style speaker recognition database. This database is useful for session variability, multi-style speaker recognition and short utterance based SV studies. Initial results are reported over the database for the three different modes of SV. A copy of the database can be obtained by contacting the authors.     

基于支持向量机的计算机键盘用户身份验真

口令认证因为简便易实现而被大多数计算机系统所采用，但容易被盗用，存在着严重的安全隐患，而利用对用户的键入特性的识别，可以大大加强口令认证的可靠性，在对国内外众多学者所做工作研究的基础上，鉴于支持向量机在进行模式识别对所具有的优良性能，提出利用支持向量机进行键入特性验真，并通过实验将其与BP，RBF，PNN和LVQ四种神经网络模型进行比较，证实采用SVM进行键入特性验真的有效性，因而其具有广阔的应用前景。     

基于关键引用验证的分布式实时垃圾搜集器*

提出了一种新的分布式垃圾搜集器（GC）机制,即基于关键引用验证的分布式GC。性能分析说明,与以往的分布式GC相比,该算法能以最短的时间延迟回收循环垃圾。尽管该算法为保留引用列表和验证过程需要额外的一些存储空间,但具有一定的实时性和较好的容错性,综合性能较好,适用于大规模分布式系统。     

Text-dependent speaker identification based on input/output HMMs: An empirical study

In this paper, we explore theInput/Output HMM (IOHMM) architecture for a substantial problem, that of text-dependent speaker identification. For subnetworks modeled with generalized linear models, we extend the IRLS algorithm to the M-step of the corresponding EM algorithm. Experimental results show that the improved EM algorithm yields significantly faster training than the original one. In comparison with the multilayer perceptron, the dynamic programming technique and hidden Markov models, we empirically demonstrate that the IOHMM architecture is a promising way to text-dependent speaker identification.     

A user authentication system using back-propagation network

Information security has been a critical issue in the field of information systems. One of the key factors in the security of a computer system is how to identify the authorization of users. Password-based user authentication is widely used to authenticate a legitimate user in the current system. In conventional password-based user authentication schemes, a system has to maintain a password table or verification table which stores the information of users IDs and passwords. Although the one-way hash functions and encryption algorithms are applied to prevent the passwords from being disclosed, the password table or verification table is still vulnerable. In order to solve this problem, in this paper, we apply the technique of back-propagation network instead of the functions of the password table and verification table. Our proposed scheme is useful in solving the security problems that occurred in systems using the password table and verification table. Furthermore, our scheme also allows each user to select a username and password of his/her choice.