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A Kalman Smoothing Algorithm for Speech Enhancement Based on the Properties of Vocal Tract Varying Slowly

A Kalman Smoothing Algorithm for Speech Enhancement Based on...

引用

ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed computing (SNPD)

作者： Hui Li Xin Wang Bei-qian Dai Wei Lu MOE-Microsoft Key Laboratory of Multimedia Computing and Communication University of Science and Technology China

The linear prediction coefficients obtained from noisy speech have an important impact on improving the quality of the enhanced speech in the speech enhancement algorithm based on the Kalman Smoother. According to the properties of the slow changes of the vocal tract, this paper proposes a novel Kalman smoothing algorithm for speech enhancement based on vocal tract parameters smoother. Firstly, the linear prediction coefficients are converted into the line spectrum frequency parameters. Then, these parameters of the adjacent frames are smoothed before they transform into state transition matrix. Experimental results indicate that the proposed Kalman smoothing algorithm for speech enhancement based on vocal tract parameters smoother can suppress the sudden changes of residual noise energy and improve the quality of enhanced speech. The quality of the enhanced speech is evaluated by means of segmental SNR and ITU-PESQ scores. Experimental results indicate that the proposed algorithm achieves obvious improvements compared with conventional Wiener filter.

关键词： Kalman filters Smoothing methods Speech enhancement Signal processing algorithms Noise shaping Wiener filter Linear predictive coding Degradation Signal processing Additive noise

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A Robust Algorithm for Iris Localization Based on Radial Symmetry

A Robust Algorithm for Iris Localization Based on Radial Sym...

引用

International Conference on Computational Intelligence and Security Workshops (CISW)

作者： Wencong Zhang Bin Li Xueyi Ye Zhenquan Zhuang MOE-Microsoft Key Laboratory of Multimedia Computing and Communication University of Science and Technology Hefei China

Previous algorithms have good localization performance for iris images captured in the ideal condition. However, in practice, the quality of iris image is greatly influenced by luminance, eyelashes, hair or glasses frame, which is easy to cause mis- localization. In order to improve the robustness of iris localization, this paper proposes a new localization algorithm based on the radial symmetry transform, in which the radial symmetry characteristic of the pupil is fully used to realize iris localization. Experimental results show that the proposed algorithm can efficiently avoid the interference of luminance and other bad conditions, and realize robust precise localization in a real-time system.

关键词： Robustness Iris recognition Eyelashes Hair Glass Integral equations Real time systems Biometrics Feature extraction Computational intelligence

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Motif Extraction with Indicative Events for System Call Sequence Classification

Motif Extraction with Indicative Events for System Call Sequ...

引用

International Conference on Fuzzy Systems and Knowledge Discovery (FSKD)

作者： Jiwei Li Xianghua Zhang Chun Yuan Zhaohui Jiang Huanqing Feng MOE-MS Key Laboratory of Multimedia Computing and Communication University of Science and Technology Hefei China Sigema Center Microsoft Research Asia Beijing China

Various approaches have been proposed to extract patterns from system call sequences invoked by applications to better model their behaviors. They use fixed-length or variable-length patterns to represent the sequences. However, these techniques are all based on mathematical rules and do not consider the underlying mechanism of the program execution. In this paper, we propose a method that extracts the motifs - subroutines conserved across sequences - in an efficient way by using the semantic call graph model. We focus on two cases: one is intrusion detection; the other is automatic problem diagnosis, and show that the presences of our defined motifs are highly discriminative features to represent different application behaviors. This is in agreement with the idea that taking these motifs to be the building blocks of program execution. Using these features, we can achieve higher detection rate while maintaining lower false positive.

关键词： Feature extraction Laboratories multimedia computing Intrusion detection Proteins Asia Application software Computerized monitoring Security Classification algorithms

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AN ITERATIVE ALGORITHM FOR ROBUST KERNEL PRINCIPAL COMPONENT ANALYSIS

AN ITERATIVE ALGORITHM FOR ROBUST KERNEL PRINCIPAL COMPONENT...

引用

2007 International Conference on Machine Learning and Cybernetics(IEEE第六届机器学习与控制论国际会议)

作者： LEI WANG NENG-HAI YU DAO-YI SHEN YAN-WEI PANG MOE-MS Key Laboratory of Multimedia Computing and Communication Department of Electronic Engineerin School of Electronic Information Engineering Tianjin University Tianjin 300072 China

Principal Component Analysis (PCA) has been proven to be an efficient method in dimensionality reduction, feature extraction and pattern *** Principal Component Analysis (KPCA) can be considered as a natural nonlinear generalization of PCA, which performs linear PCA in a high dimensional space implicitly by using kernel ***, both conventional PCA and KPCA suffer from the deficiency of being sensitive to *** robust KPCA has to eigen-decompose the Gram matrix directly in each step and is much more computationally infeasible due to the large size of the matrix when the number of training samples is *** extending existing robust PCA algorithm using kernel methods, we present a novel robust adaptive algorithm for calculating the kernel principal *** proposed method not only preserves the characteristic of capturing underlying nonlinear structure of KPCA but also is robust against outliers by restraining the effect of outlying *** with existing robust KPCA methods, our method is performed without having to store the kernel matrix, which can reduce significantly the storage *** addition, our method shows the potential of expansibility to the incremental learning *** results on synthetic data indicate that our improved algorithm is effective and promising.

关键词： Robust principal component analysis Robust kernel principal component analysis Outliers Dimensionality reduction Feature extraction

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A Segmentation Posterior Based Endpointing Algorithm

A Segmentation Posterior Based Endpointing Algorithm

引用

International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： YanLu Xie Yu Shi Frank K. Soong BeiQian Dai Moe-MS Key Laboratory of Multimedia Computing and Communication University of Science and Technology Hefei China Microsoft Research Asia University of Science and Technology Beijing China

A segmentation posterior probability based endpointing algorithm for robust ASR is proposed. First, each speech signal is partitioned into homogeneous segments via auto-segmentation. Then posterior probabilities of all possible endpoints are computed, based on the segmentation likelihoods of all levels in a selected range. Endpoints with the highest posterior probabilities are finally selected. The new method differs from the previous auto-segmentation and clustering based algorithm on that the former considers hypotheses from several levels, while the latter depends only on one appropriate level. Another potential benefit of the proposed method is that any endpointing or VAD results can be integrated, as hypotheses, into the posterior probability framework. Experiments based on the AURORA2 digit database show the robustness of the proposed method.

关键词： Partitioning algorithms Speech recognition Clustering algorithms Telecommunication standards Databases Background noise Higher order statistics Speech enhancement Asia Laboratories

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A STATISTICAL ANALYSIS ON DIFFERENTIAL SIGNALS FOR NOISE LEVEL ESTIMATION

A STATISTICAL ANALYSIS ON DIFFERENTIAL SIGNALS FOR NOISE LEV...

引用

2007 International Conference on Machine Learning and Cybernetics(IEEE第六届机器学习与控制论国际会议)

作者： WEI-HAI LI BO WANG MOE-Microsoft Key Laboratory of Multimedia Computing and Communication University of Science and Technology of China Hefei 230027 China

A new noise level estimating method based on a statistical analysis is proposed *** this method, the noise characteristics are obtained by matching theoretical distribution curve to differential signal *** an example, the problem is addressed to additive white Gaussian noise in digital images, and the noise variance is *** efficiency of this method is verified by the accurate experiment results.

关键词： Noise level estimation Gaussian distribution Difference analysis Statistical histogram Curve match

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Anisotropic Manifold Ranking for Video Annotation

Anisotropic Manifold Ranking for Video Annotation

引用

IEEE International Conference on multimedia and Expo (ICME)

作者： Jinhui Tang Xian-Sheng Hua Guo-Jun Qi Tao Mei Xiuqing Wu MOE-Microsoft Key Laboratory of Multimedia Computing and Communication University of Science and Technology Hefei China Microsoft Research Asia Beijing China

Graph-based semi-supervised learning (SSL) has attracted lots of interests in machine learning community as well as many application areas including video annotation recently. However, one of the two basic assumptions, structure assumption, which is an essential point of graph-based SSL, is not embedded into the pairwise similarity measure. Accordingly, we propose a novel graph-based SSL method for video annotation, named anisotropic manifold ranking (AniMR), based on a structure-related similarity measure. This method takes the influence of the density difference between samples into account to improve the pairwise similarity. Furthermore, we will show that AniMR can also be deduced from partial differential equation (PDE) based anisotropic diffusion. It demonstrates that the label propagation in AniMR is anisotropic, which is intrinsically different from the isotropic label propagation process in general graph-based SSL methods. Experiments conducted on the TRECVID data set show this approach outperforms ordinary graph-based SSL methods and is effective for video semantic annotation.

关键词： Anisotropic magnetoresistance multimedia computing Asia Semisupervised learning Machine learning Laboratories Partial differential equations Feature extraction Iterative methods

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Multi-Graph Semi-Supervised Learning for Video Semantic Feature Extraction

Multi-Graph Semi-Supervised Learning for Video Semantic Feat...

引用

IEEE International Conference on multimedia and Expo (ICME)

作者： Meng Wang Xian-Sheng Hua Xun Yuan Yan Song Li-Rong Dai MOE-Microsoft Key Laboratory of Multimedia Computing and Communication University of Science and Technology China Microsoft Research Asia Beijing P.R

This paper proposes a video semantic feature extraction approach based on multi-graph semi-supervised learning, which aims to simultaneously deal with the insufficiency of training data and the curse of dimensionality. In contrast to traditional graph-based semi-supervised learning, which generates graph from high-dimensional low-level features, we separate the original low-level features into multiple modalities with minimum correlations, and thus multiple graphs are obtained from these modalities. This way can tackle the curse of dimensionality brought by the high-dimensional feature space. We then propose a criterion to optimally fuse these graphs based on the pairwise relationships among training samples, and implement semi-supervised learning on the fused graph. Experimental results have demonstrated the effectiveness of the proposed approach.

关键词： Semisupervised learning Feature extraction Training data Video compression Fuses Degradation Laboratories multimedia computing Asia Large-scale systems

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Quality Assessment for Image Coding Based on Matching Pursuit

Quality Assessment for Image Coding Based on Matching Pursui...

引用

IEEE International Conference on multimedia and Expo (ICME)

作者： Jianxin Pang Rong Zhang Lu Lu Zhengkai Liu MOE-Microsoft Key Laboratory of Multimedia Computing and Communication Department of Electronic Engineering and Information Science University of Science and Technology Hefei Anhui China

Valuation of image coding relies on not only the efficiency of the coding, but also the quality of the coded image. We present a new objective quality assessment metric for image coding based on matching pursuit. First of all, we get the characteristics of the most important structure by projecting the reference image onto the base functions from a dictionary using matching pursuit. Secondly, we process the reference image and gain the structure information of the images in the order of importance, projecting the images onto the structural characteristics. Finally the objective quality score is given by comparing the differences of structure information between the reference and coded images. Experimental results show that the proposed approach is well consistent with the subjective quality score.

关键词： Quality assessment Image coding Matching pursuit algorithms Image quality Humans Layout Image segmentation PSNR Laboratories multimedia computing

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Lazy Learning Based Efficient Video Annotation

Lazy Learning Based Efficient Video Annotation

引用

IEEE International Conference on multimedia and Expo (ICME)

作者： Meng Wang Xian-Sheng Hua Yan Song Richang Hong Li-Rong Dai MOE-Microsoft Key Laboratory of Multimedia Computing and Communication University of Science and Technology China Microsoft Research Asia Beijing P.R. China

Eager learning methods, such as SVM, are widely applied in video annotation task for their substantial performance. However, their computational costs are usually prohibitive when a large dataset is faced, especially when annotating a large lexicon of semantic concepts. This paper proposes a video annotation scheme based on lazy learning, and shows that this scheme is much more computationally efficient and flexible. Based on a recently proposed improved Parzen window method, we provide a lazy learning based video annotation scheme. After building the pairwise relationships in dataset, the annotation can be finished rapidly for each concept. Experiments show that the proposed method is much more efficient than SVM while retaining comparable performance.

关键词： Support vector machines Learning systems Video compression Computational efficiency Laboratories multimedia computing Asia Large-scale systems Information retrieval Feature extraction

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