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2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)最新文献

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Compressive graph clustering from random sketches 随机草图的压缩图聚类
2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) Pub Date : 2015-04-19 DOI: 10.1109/ICASSP.2015.7179016
Yuejie Chi
{"title":"Compressive graph clustering from random sketches","authors":"Yuejie Chi","doi":"10.1109/ICASSP.2015.7179016","DOIUrl":"https://doi.org/10.1109/ICASSP.2015.7179016","url":null,"abstract":"Graph clustering, where the goal is to cluster the nodes in a graph into disjoint clusters, arises from applications such as community detection, network monitoring, and bioinformatics. This paper describes an approach for graph clustering based on a small number of linear measurements, i.e. sketches, of the adjacency matrix, where each sketch corresponds to the number of edges in a randomly selected subgraph. Under the stochastic block model, we propose a computationally tractable algorithm based on semidefinite programming to recover the underlying clustering structure, by motivating the low-dimensional parsimonious structure of the clustering matrix. Numerical examples are presented to validate the excellent performance of the proposed algorithm, which allows exact recovery of the clustering matrix under favorable trade-offs between the number of sketches and the edge density gap under the stochastic block model.","PeriodicalId":117666,"journal":{"name":"2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132233395","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 4
Accurate kernel-based spectrum sensing for Gaussian and non-Gaussian noise models 高斯和非高斯噪声模型的精确核频谱感知
2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) Pub Date : 2015-04-19 DOI: 10.1109/ICASSP.2015.7178552
Argin Margoosian, J. Abouei, K. Plataniotis
{"title":"Accurate kernel-based spectrum sensing for Gaussian and non-Gaussian noise models","authors":"Argin Margoosian, J. Abouei, K. Plataniotis","doi":"10.1109/ICASSP.2015.7178552","DOIUrl":"https://doi.org/10.1109/ICASSP.2015.7178552","url":null,"abstract":"This paper introduces a spectrum sensing scenario based on kernel theory which compares favorably against the conventional Energy Detector (ED) in a cognitive radio system. The so-called Kerenlized Energy Detector (KED) can provide superior accuracy in the case of non-Gaussian noise. The incorporation of the nonlinear kernel function in the KED test statistics allows for the development of a nonlinear algorithm capable of considering both higher order and Fractional Lower Order Moments (FLOMs) in the sensing task. Simulation results show that the proposed semi-blind kernelized spectrum sensing algorithm is much robust against impulsive noises and displays a considerably better detection performance than the conventional ED in practical impulsive man-made noises which are generally modeled as the Laplacian and the α-stable distributions. Moreover, for the Gaussian signal and noise model, the performance of the KED scheme is almost identical to that of the conventional ED.","PeriodicalId":117666,"journal":{"name":"2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","volume":"146 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132463904","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 10
Efficient construction of dictionaries for kernel adaptive filtering in a dynamic environment 动态环境下核自适应滤波字典的高效构造
2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) Pub Date : 2015-04-19 DOI: 10.1109/ICASSP.2015.7178629
Taichi Ishida, Toshihisa Tanaka
{"title":"Efficient construction of dictionaries for kernel adaptive filtering in a dynamic environment","authors":"Taichi Ishida, Toshihisa Tanaka","doi":"10.1109/ICASSP.2015.7178629","DOIUrl":"https://doi.org/10.1109/ICASSP.2015.7178629","url":null,"abstract":"One of the major challenges in kernel adaptive filtering is how to construct an efficient dictionary of observed input signals. In this paper, we propose novel dictionary adaptation rules for kernel adaptive filtering. The first algorithm can efficiently “move” elements of the dictionary to increase the approximation performance. The second algorithm mainly focuses on a nonstationary system, which can yield the increase of the dictionary size. The proposed method can eliminate unnecessary elements in the dictionary. Numerical examples support the efficacy of the proposed methods.","PeriodicalId":117666,"journal":{"name":"2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132468244","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 6
Cognitive biases in Bayesian updating and optimal information sequencing 贝叶斯更新与最优信息排序中的认知偏差
2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) Pub Date : 2015-04-19 DOI: 10.1109/ICASSP.2015.7178741
Sara Mourad, A. Tewfik
{"title":"Cognitive biases in Bayesian updating and optimal information sequencing","authors":"Sara Mourad, A. Tewfik","doi":"10.1109/ICASSP.2015.7178741","DOIUrl":"https://doi.org/10.1109/ICASSP.2015.7178741","url":null,"abstract":"In this paper, we consider the problem of optimally ordering information to a human subject to maximize detection performance in a binary hypothesis testing problem. We begin by proposing a modification of the traditional Bayesian solution to hypothesis testing problems to incorporate the effect of human cognitive biases. Next, we consider the problem of selecting a subset of information to maximize detection performance in truncated hypothesis testing problems. We then use the solution to that problem to determine the real time ordering of information to enhance human binary hypothesis testing. We verify through simulations that the proposed ordering methods with and without cognitive biases minimize the probability of miss and the probability of false alarm.","PeriodicalId":117666,"journal":{"name":"2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","volume":"298 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134421438","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Closed-form Cramer-Rao lower bounds for DOA estimation from turbo-coded square-QAM-modulated transmissions 涡轮编码方形qam调制传输的DOA估计的闭形式Cramer-Rao下界
2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) Pub Date : 2015-04-19 DOI: 10.1109/ICASSP.2015.7178620
F. Bellili, Chaima Elguet, Souheib Ben Amor, S. Affes, A. Stephenne
{"title":"Closed-form Cramer-Rao lower bounds for DOA estimation from turbo-coded square-QAM-modulated transmissions","authors":"F. Bellili, Chaima Elguet, Souheib Ben Amor, S. Affes, A. Stephenne","doi":"10.1109/ICASSP.2015.7178620","DOIUrl":"https://doi.org/10.1109/ICASSP.2015.7178620","url":null,"abstract":"This paper tackles the problem of the direction of arrival (DOA) estimation in turbo-coded systems. We derive for the first time the closed-form expressions for the Cramér-Rao lower bounds (CRLBs) of the code-aided (CA) DOA estimates from arbitrary square-QAM modulated signals. We succeed in factorizing the likelihood function of the system into two analogous terms linearizing thereby all the derivation steps of the Fisher information (FI) element. Simulation results demonstrate that the CRLB for the CA DOA estimates lies between its counterparts in non-data-aided (NDA) and data-aided (DA) estimation schemes. Moreover, the DOA CA CRLB improves by decreasing the coding rate highlighting thereby the potential gain in estimation performance stemming from the proper exploitation of the decoder output.","PeriodicalId":117666,"journal":{"name":"2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133949286","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 4
Integrating Gaussian mixtures into deep neural networks: Softmax layer with hidden variables 在深度神经网络中集成高斯混合:带隐变量的Softmax层
2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) Pub Date : 2015-04-19 DOI: 10.1109/ICASSP.2015.7178779
Zoltán Tüske, Muhammad Ali Tahir, R. Schlüter, H. Ney
{"title":"Integrating Gaussian mixtures into deep neural networks: Softmax layer with hidden variables","authors":"Zoltán Tüske, Muhammad Ali Tahir, R. Schlüter, H. Ney","doi":"10.1109/ICASSP.2015.7178779","DOIUrl":"https://doi.org/10.1109/ICASSP.2015.7178779","url":null,"abstract":"In the hybrid approach, neural network output directly serves as hidden Markov model (HMM) state posterior probability estimates. In contrast to this, in the tandem approach neural network output is used as input features to improve classic Gaussian mixture model (GMM) based emission probability estimates. This paper shows that GMM can be easily integrated into the deep neural network framework. By exploiting its equivalence with the log-linear mixture model (LMM), GMM can be transformed to a large softmax layer followed by a summation pooling layer. Theoretical and experimental results indicate that the jointly trained and optimally chosen GMM and bottleneck tandem features cannot perform worse than a hybrid model. Thus, the question “hybrid vs. tandem” simplifies to optimizing the output layer of a neural network. Speech recognition experiments are carried out on a broadcast news and conversations task using up to 12 feed-forward hidden layers with sigmoid and rectified linear unit activation functions. The evaluation of the LMM layer shows recognition gains over the classic softmax output.","PeriodicalId":117666,"journal":{"name":"2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","volume":"84 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134092128","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 40
Neighborhood regression for edge-preserving image super-resolution 边缘保持图像超分辨率的邻域回归
2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) Pub Date : 2015-04-19 DOI: 10.1109/ICASSP.2015.7178160
Yanghao Li, Jiaying Liu, Wenhan Yang, Zongming Guo
{"title":"Neighborhood regression for edge-preserving image super-resolution","authors":"Yanghao Li, Jiaying Liu, Wenhan Yang, Zongming Guo","doi":"10.1109/ICASSP.2015.7178160","DOIUrl":"https://doi.org/10.1109/ICASSP.2015.7178160","url":null,"abstract":"There have been many proposed works on image super-resolution via employing different priors or external databases to enhance HR results. However, most of them do not work well on the reconstruction of high-frequency details of images, which are more sensitive for human vision system. Rather than reconstructing the whole components in the image directly, we propose a novel edge-preserving super-resolution algorithm, which reconstructs low- and high-frequency components separately. In this paper, a Neighborhood Regression method is proposed to reconstruct high-frequency details on edge maps, and low-frequency part is reconstructed by the traditional bicubic method. Then, we perform an iterative combination method to obtain the estimated high resolution result, based on an energy minimization function which contains both low-frequency consistency and high-frequency adaptation. Extensive experiments evaluate the effectiveness and performance of our algorithm. It shows that our method is competitive or even better than the state-of-art methods.","PeriodicalId":117666,"journal":{"name":"2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","volume":"407 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134353337","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 14
Estimation of multipath propagation delays and interaural time differences from 3-D head scans 三维头部扫描的多径传播延迟和间隔时间差估计
2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) Pub Date : 2015-04-19 DOI: 10.1109/ICASSP.2015.7178019
H. Gamper, Mark R. P. Thomas, I. Tashev
{"title":"Estimation of multipath propagation delays and interaural time differences from 3-D head scans","authors":"H. Gamper, Mark R. P. Thomas, I. Tashev","doi":"10.1109/ICASSP.2015.7178019","DOIUrl":"https://doi.org/10.1109/ICASSP.2015.7178019","url":null,"abstract":"The estimation of acoustic propagation delays from a sound source to a listener's ear entrances is useful for understanding and visualising the wave propagation along the surface of the head, and necessary for individualised spatial sound rendering. The interaural time difference (ITD) is of particular research interest, as it constitutes one of the main localisation cues exploited by the human auditory system. Here, an approach is proposed that employs ray tracing on a 3-D head scan to estimate and visualise the propagation delays and ITDs from a sound source to a subject's ear entrances. Experimental results indicate that the proposed approach is computationally efficient, and performs equally well or better than optimally tuned parametric ITD models, with a mean absolute ITD estimation error of about 14μs.","PeriodicalId":117666,"journal":{"name":"2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134375679","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 7
Ocean acoustic waveguide invariant parameter estimation using tonal noise sources 基于调性噪声源的海声波导不变参数估计
2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) Pub Date : 2015-04-19 DOI: 10.1109/ICASSP.2015.7178722
Andrew Harms, J. L. Odom, J. Krolik
{"title":"Ocean acoustic waveguide invariant parameter estimation using tonal noise sources","authors":"Andrew Harms, J. L. Odom, J. Krolik","doi":"10.1109/ICASSP.2015.7178722","DOIUrl":"https://doi.org/10.1109/ICASSP.2015.7178722","url":null,"abstract":"The abundance of shipping noise sources in ocean littoral zones provides a great opportunity to estimate ocean environmental parameters. The waveguide invariant parameter β, defined as the ratio of inverse group and phase velocities between modes, has been used in a variety of applications including ranging of passive sources. Previous work utilizing the waveguide invariant in passive sonar has relied on processing the time-frequency intensity striations of broadband sources. In this paper, the reception of strong tonal components from transiting commercial ships of known location (e.g., from AIS data) are used for estimating β over the source-receiver path. A maximum likelihood estimate of β is derived by relating the fading characteristics of different tonal components over range. The method is verified on simulated data using a Pekeris waveguide model.","PeriodicalId":117666,"journal":{"name":"2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129388035","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 7
JFA modeling with left-to-right structure and a new backend for text-dependent speaker recognition 具有从左到右结构的JFA建模和用于依赖文本的说话人识别的新后端
2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) Pub Date : 2015-04-19 DOI: 10.1109/ICASSP.2015.7178860
P. Kenny, Themos Stafylakis, Md. Jahangir Alam, M. Kockmann
{"title":"JFA modeling with left-to-right structure and a new backend for text-dependent speaker recognition","authors":"P. Kenny, Themos Stafylakis, Md. Jahangir Alam, M. Kockmann","doi":"10.1109/ICASSP.2015.7178860","DOIUrl":"https://doi.org/10.1109/ICASSP.2015.7178860","url":null,"abstract":"This paper introduces a new formulation of Joint Factor Analysis (JFA) for text-dependent speaker recognition based on left-to-right modeling with tied mixture HMMs. It accommodates many different ways of extracting multiple features to characterize speakers (features may or may not be HMM state-dependent, they may be modeled with subspace or factorial priors and these priors maybe imputed from text-dependent or text-independent background data). We feed these features to a new, trainable classifier for text-dependent speaker recognition in a manner which is broadly analogous to the i-vector/PLDA cascade in text-independent speaker recognition. We have evaluated this approach on a challenging proprietary dataset consisting of telephone recordings of short English and Urdu pass-phrases collected in Pakistan. By fusing results obtained with multiple front ends, equal error rate of around 2% are achievable.","PeriodicalId":117666,"journal":{"name":"2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129408900","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 11
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