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2017 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)最新文献

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Distinction between healthy individuals and patients with confident abnormal respiration 健康个体与自信呼吸异常患者的区别
Masara Yamashita, Tasuku Miura, S. Matsunaga
To adequately distinguish between healthy individuals and patients with respiratory disorders, we propose a new classification method combining two conventional methods. The first method entails determining the presence of a "confident abnormal respiration" period (used to describe individuals for whom the likelihood of an abnormal respiratory candidate was much higher than for that of a normal candidate, and for which patients could be determined with high accuracy). The second method entails comparing the two total likelihoods (through a series of inspiration and expiration periods) of normal and abnormal candidates of each respiratory period in a test sample. In our new method, if one or more confident abnormal respiration phases are detected in a test respiration sample, the first method is used; otherwise, the second method is used for the classification. Our proposed method achieved significantly higher performance (88.6%) at the 5% level (p=0.027) than does each conventional classification method alone (80.6% and 84.9%). This validates our newly proposed classification method.
为了充分区分健康个体和呼吸系统疾病患者,我们提出了一种结合两种传统方法的新分类方法。第一种方法需要确定是否存在“确信的呼吸异常”时期(用于描述异常呼吸候选者的可能性远远高于正常候选者的可能性,并且可以以高准确性确定患者的个体)。第二种方法需要比较测试样本中每个呼吸周期的正常和异常候选者的两个总可能性(通过一系列吸气和呼气周期)。在我们的新方法中,如果在测试呼吸样本中检测到一个或多个可靠的异常呼吸阶段,则使用第一种方法;否则,使用第二种方法进行分类。在5%的水平上(p=0.027),我们提出的方法比单独使用每种传统分类方法(80.6%和84.9%)取得了显著更高的性能(88.6%)。这验证了我们新提出的分类方法。
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引用次数: 0
QoE-estimation models for video streaming services 视频流服务的qos估计模型
Kazuhisa Yamagishi
As encoders and decoders (codecs), networks, and displays have become more technologically advanced, network and video-streaming-service providers have been able to provide video-streaming services over a network (e.g., fiber-to-the home and long-term evolution); therefore, the use of these services has been increasing drastically in the past decade. To maintain the high quality of experience (QoE) of these services, network and service providers need to invest in equipment (e.g., network devices, codecs, and servers). To increase return on investment, the QoE of these services needs to be appropriately designed with as little investment as possible, and its normality needs to be monitored while services are provided. In general, the QoE of these services degrades due to compression and network conditions (e.g., packet loss and delay). Therefore, it is necessary to develop a QoE-estimation model by taking into account the impact of compression and network on quality. This paper introduces subjective-quality-assessment methods and QoE-estimation models that assess user QoE in video-streaming services and standardization activities.
随着编码器和解码器(编解码器)、网络和显示器在技术上变得更加先进,网络和视频流服务提供商已经能够通过网络(例如光纤到户和长期演进)提供视频流服务;因此,这些服务的使用在过去十年中急剧增加。为了保持这些服务的高质量体验(QoE),网络和服务提供商需要投资于设备(例如,网络设备、编解码器和服务器)。为了增加投资回报,需要以尽可能少的投资适当地设计这些服务的QoE,并且在提供服务时需要监视其正常性。通常,由于压缩和网络条件(例如,数据包丢失和延迟),这些服务的QoE会降低。因此,有必要建立一个考虑压缩和网络对质量影响的qos估计模型。介绍了视频流服务和标准化活动中用户质量评价的主观质量评价方法和质量评价模型。
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引用次数: 3
Two-dimensional winner-takes-all hashing in template protection based on fingerprint and voice feature level fusion 基于指纹和语音特征级融合的二维赢者通吃的模板保护算法
K. Chee, Zhe Jin, W. Yap, B. Goi
Biometrics has been explosively deployed for identity verification and/or identification over the last decade. Lately, multi-biometric systems are gaining attention due to its universality and higher accuracy in biometric recognition. However, the compromise of templates stored in database as separate entities in multi-biometric systems undoubtedly poses the major security and privacy threats due to the strong binding between identity and biometric data. In this paper, we propose to fuse fingerprint and voice modalities at feature level to obtain an integrated template. Subsequently, we propose two-dimensional Winner-Takes-All hashing method to protect the fused template. The proposed hashing method is inspired from Winner-Takes-All hashing and further altered for this unique multi-biometric system. Specifically, the proposed hashing method transforms the continuous fused biometric feature into discrete value. Such transformation enjoys strong non-linearity and thus resilient to the feature variation in certain degree. We show that the resultant hashed code can withstand the major attacks (e.g. template invertibility attack, attack via multiplicity etc.) while yielding reasonable recognition performance. A low equal error rate of 0.94% is obtained using the proposed hashing method on fingerprint images from FVC2002 DB1 and FVC2002 DB2 datasets and voice features from NIST Speaker Recognition Evaluation (SRE) 2004 ∼ 2010. More importantly, the proposed two-dimensional Winner-Takes-All hashing method can be extended and applied to other biometric modalities with real value representation.
在过去的十年里,生物识别技术在身份验证和/或身份识别方面得到了爆炸式的应用。近年来,多生物特征系统因其在生物特征识别中的通用性和较高的准确性而备受关注。然而,在多生物识别系统中,由于身份与生物识别数据之间的强绑定,作为独立实体存储在数据库中的模板泄露无疑构成了重大的安全和隐私威胁。在本文中,我们提出在特征级融合指纹和语音模式,以获得一个集成的模板。随后,我们提出了二维赢者通吃的哈希方法来保护融合模板。所提出的哈希方法受到赢家通吃哈希法的启发,并针对这种独特的多生物识别系统进行了进一步的修改。具体来说,提出的哈希方法将连续融合的生物特征转化为离散值。这种变换具有较强的非线性,对特征变化有一定的弹性。我们证明了所得到的哈希代码可以承受主要的攻击(例如模板可逆性攻击,通过多重性攻击等),同时产生合理的识别性能。利用所提出的散列方法,对来自FVC2002 DB1和FVC2002 DB2数据集的指纹图像和来自NIST Speaker Recognition Evaluation (SRE) 2004 ~ 2010的语音特征进行了哈希处理,获得了0.94%的低等错误率。更重要的是,所提出的二维“赢者通吃”哈希方法可以扩展并应用于其他具有实值表示的生物识别模式。
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引用次数: 5
Topic embedding of sentences for story segmentation 面向故事分割的句子主题嵌入
J. Yu, Xiong Xiao, Lei Xie, Chng Eng Siong
In this paper, we propose to embed sentences into fixed-dimensional vectors that carry the topic information for story segmentation. As a sentence comprises of a sequence of words and may have different lengths, we use long short-term memory recurrent neural network (LSTM-RNN) to summarize the information of the whole sentence and only predict the topic class at the last word in the sentence. The output of the network at the last word can be used as an embedding of the sentence in the topic space. We used the obtained sentence embeddings in the HMM-based story segmentation framework and obtained promising results. On the TDT2 corpus, the F1 measure is improved to 0.789 from 0.765 which is obtained by a competitive system using DNN and bag-of-words features.
在本文中,我们提出将句子嵌入到承载主题信息的固定维向量中进行故事分割。由于一个句子由一系列单词组成,并且可能有不同的长度,我们使用长短期记忆递归神经网络(LSTM-RNN)来总结整个句子的信息,只预测句子中最后一个单词的主题类。网络在最后一个单词的输出可以作为句子在主题空间的嵌入。我们将得到的句子嵌入应用到基于hmm的故事分割框架中,取得了令人满意的结果。在TDT2语料库上,F1度量从使用DNN和词袋特征的竞争系统获得的0.765改进到0.789。
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引用次数: 1
Digital computation of fractional Fourier and linear canonical transforms and sparse image representation 分数傅里叶和线性正则变换的数字计算和稀疏图像表示
Aykut Koç, Haldun M. Özaktas, Burak Bartan, Erhan Gundogdu, T. Çukur
Fast and accurate digital computation of the fractional Fourier transform (FRT) and linear canonical transforms (LCT) are of utmost importance in order to deploy them in real world applications and systems. The algorithms in O(NlogN) to obtain the samples of the transform from the samples of the input function are presented for several different types of FRTs and LCTs, both in 1D and 2D forms. To apply them in image processing we consider the problem of obtaining sparse transform domains for images. Sparse recovery tries to reconstruct images that are sparse in a linear transform domain, from an underdeter- mined measurement set. The success of sparse recovery relies on the knowledge of domains in which compressible representations of the image can be obtained. In this work, we consider two- and three-dimensional images, and investigate the effects of the fractional Fourier (FRT) and linear canonical transforms (LCT) in obtaining sparser transform domains. For 2D images, we investigate direct transforming versus several patching strategies. For the 3D case, we consider biomedical images, and compare several different strategies such as taking 2D slices and optimizing for each slice and direct 3D transforming.
分数阶傅立叶变换(FRT)和线性正则变换(LCT)的快速、准确的数字计算对于将它们应用到实际应用和系统中至关重要。针对几种不同类型的frt和lct,给出了在O(NlogN)内从输入函数的样本中获取变换样本的算法,包括1D和2D形式。为了将它们应用到图像处理中,我们考虑了图像稀疏变换域的获取问题。稀疏恢复试图从一个被破坏的测量集重建在线性变换域中稀疏的图像。稀疏恢复的成功依赖于可以获得图像可压缩表示的域的知识。在这项工作中,我们考虑了二维和三维图像,并研究了分数傅里叶变换(FRT)和线性正则变换(LCT)在获得更稀疏变换域中的作用。对于二维图像,我们研究了直接变换与几种修补策略。对于三维情况,我们考虑了生物医学图像,并比较了几种不同的策略,如取二维切片并对每个切片进行优化和直接三维变换。
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引用次数: 1
Compressed sensing reconstruction of MR phase-varied images using multi-scale complex sparsifying transform 基于多尺度复稀疏化变换的MR相变图像压缩感知重构
S. Ito
The use of compressive sensing (CS) in applications with rapid spatial phase variations is difficult, since not only the magnitude but also phase regularization is required in the CS framework. In this article, we propose a novel image reconstruction scheme for MR phase varied images in which phase regularizer is not required in the rather simple CS reconstruction scheme. In our work, to improve the incoherence between the sampling matrix and the basis of the sparsifying transform, multi-scale eFREBAS transform domain thresholding was used. Reconstruction experiments showed that CS reconstruction using 8-scale eFREBAS transform can restore the magnitude and phase of images much better than the conventional method, especially at the region where phase changes rapidly
压缩感知(CS)在空间相位快速变化的应用中使用是困难的,因为在压缩感知框架中不仅需要幅度,而且需要相位正则化。在本文中,我们提出了一种新的MR相位变化图像重建方案,该方案在相当简单的CS重建方案中不需要相位正则化器。为了改善采样矩阵与稀疏化变换基之间的不相干性,本文采用了多尺度eFREBAS变换域阈值分割方法。重建实验表明,采用8尺度eFREBAS变换的CS重建方法可以较好地恢复图像的幅度和相位,特别是在相位变化较快的区域
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引用次数: 1
Statistical-mechanical analysis of the FXLMS algorithm for multiple-channel active noise control 多通道主动噪声控制中FXLMS算法的统计力学分析
Tomoki Murata, Y. Kajikawa, S. Miyoshi
We analyze the behaviors of the Filtered-X LMS (FXLMS) algorithm for active noise control (ANC). Correlations between the impulse response of an adaptive filter and a primary path are treated as macroscopic variables. To obtain the correlations, we analytically solve the equations and finally compute the MSE. In particular, we analyze the behaviors of multiple-channel ANC. We theoretically show that the MSE is affected by the secondary paths that are not directly connected.
分析了用于主动噪声控制(ANC)的滤波- x LMS (FXLMS)算法的行为。自适应滤波器的脉冲响应与主路径之间的相关性被视为宏观变量。为了得到相关性,我们对方程进行解析求解,最后计算出均方差。特别地,我们分析了多通道ANC的行为。我们从理论上表明,MSE受到非直接连接的辅助路径的影响。
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引用次数: 4
Secure data management system with traceability against internal leakage 具有可追溯性的安全数据管理系统,防止内部泄漏
M. Kuribayashi, Takahiro Ueda, N. Funabiki
The management of sensitive data in an organization is not limited to use authentication and encrytion systems. Actually, malicious users inside of an organization will leak sensitive data to adversaries if the users are privileged to access to the data. In this study, we enable a manager to identify the traitor(s) inside of an organization from the leaked data. The essential technique is the fingerprinting for encrypted data. When a user decrypts a ciphertext using the secret key assigned to the user, the decrypted data involves the information associated with the user. We propose such an access control system by combining an attribute-based encryption scheme and fingerprinting scheme. The proposed method prevents a dishonest manager from framing innocent users by realizing the asymmetric protocol using the fingerprinting scheme based on a key management.
组织中敏感数据的管理并不局限于使用身份验证和加密系统。实际上,如果组织内部的恶意用户有权访问敏感数据,则会将敏感数据泄露给攻击者。在本研究中,我们使管理者能够从泄露的数据中识别组织内部的叛徒。关键技术是加密数据的指纹识别。当用户使用分配给该用户的密钥解密密文时,解密的数据包含与该用户相关的信息。我们提出了一种基于属性的加密方案和指纹识别方案相结合的门禁系统。该方法利用基于密钥管理的指纹方案实现非对称协议,防止不诚实的管理者陷害无辜用户。
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引用次数: 0
Design of adaptively scaled belief in large MIMO detection for higher-order modulation 高阶调制下大MIMO检测的自适应尺度信度设计
Takumi Takahashi, S. Ibi, S. Sampei
This paper proposes a new design criterion of adaptively scaled belief (ASB) in Gaussian belief propagation (GaBP), especially for large multi-user multi-input multi-output (MU-MIMO) detection with higher-order modulation. The most vital issue with regard to improving the convergence property of GaBP iterative detection is how to deal with the soft symbol outliers, which are induced by modeling errors of prior beliefs due to a lack of channel hardening effects. Unfortunately, the modeling errors become more severe in the presence of higher correlation among typical bit-wise prior beliefs while utilizing higher-order quadrature amplitude modulation (QAM) schemes. To avoid impairments of the inter-bit correlation, symbol-wise beliefs are defined for GaBP self-iterative detection. Moreover, as a simplest way to mitigate the harmful impacts of soft symbol outliers, a novel adaptive belief scaling is proposed while stabilizing dynamics of random MIMO channels. Finally, the validity of ASB for symbol-wise iterative detection is confirmed regarding suppression of the bit error rate (BER) floor level.
针对高阶调制下的大型多用户多输入多输出(MU-MIMO)检测,提出了一种新的高斯信念传播(GaBP)中自适应缩放信念(ASB)设计准则。提高GaBP迭代检测的收敛性最关键的问题是如何处理由于缺乏信道硬化效应而导致的先验信念建模误差所导致的软符号异常值。不幸的是,在使用高阶正交调幅(QAM)方案时,在典型的比特先验信念之间存在较高的相关性时,建模误差变得更加严重。为了避免位间相关性的损害,在GaBP自迭代检测中定义了符号明智信念。此外,在稳定随机MIMO信道动态的同时,提出了一种新的自适应信念尺度,作为减轻软符号异常值有害影响的最简单方法。最后,从抑制误码率(BER)的角度验证了ASB在符号迭代检测中的有效性。
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引用次数: 5
Enhanced F0 generation for GPR-based speech synthesis considering syllable-based prosodic features 考虑基于音节韵律特征的基于gpr的语音合成增强F0生成
Decha Moungsri, Tomoki Koriyama, Takao Kobayashi
The conventional frame-level Gaussian process regression (GPR)-based F0 generation can produce natural sounding pitch contours. However, a frame-level model is insufficient to represent pitch patterns in longer unit, especially for syllable- level tone contours in tonal languages. This paper proposes a multi-level modeling technique for improving GPR-based F0 generation, in which syllable-level model is considered as well as the frame-level model. In the syllable-level model, we use the discrete cosine transform (DCT) coefficients extracted from log F0 contour in syllable unit as the output variables of Gaussian process. F0 contours are generated by jointly maximizing predictive distribution of frame- and syllable-level models. Experimental results of objective evaluation show improvement in F0 generation when using a small amount of training data around 30 minutes.
传统的基于帧级高斯过程回归(GPR)的F0生成方法可以生成自然的音高轮廓。然而,框架级模型不足以表示较长单位的音高模式,特别是对于声调语言中音节级的音调轮廓。为了改进基于gpr的F0生成,本文提出了一种多级建模技术,其中考虑了音节级模型和框架级模型。在音节级模型中,我们使用从音节单位的log F0轮廓中提取的离散余弦变换(DCT)系数作为高斯过程的输出变量。F0轮廓是通过联合最大化框架级和音节级模型的预测分布来生成的。客观评价的实验结果表明,在30分钟左右使用少量训练数据时,F0生成有所改善。
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引用次数: 0
期刊
2017 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)
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