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检索条件"机构=Key Laboratory of Pattern Recognition and Intelligent System"

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Microblog retrieval based on term similarity graph

Microblog retrieval based on term similarity graph

引用

International Conference on Computer Science and Network Technology (ICCSNT)

作者： Yuhang Lin Yan Li Weiran Xu Jun Guo Pattern Recognition and Intelligent System Laboratory Beijing University of Posts and Telecommunications China

ISBN: (纸本)9781467329637

In this paper, we introduce a term similarity graph based microblog retrieval model. We propose an undirected weighted graph to describe each post where nodes represent terms and they are linked together based on the co-occurrences. Then an electric network is applied to calculate the resistance distances between pairs of terms. For a given query topic, mutual relevancy in between query terms and between term groups form the expansions to better describe the query. We also define a scoring and ranking model to improve search over large set of microblogs by considering both expanded words and tweets special attributes (hyperlinks and publish time). Our experiments use Twitter 2011 two weeks' data offered by TREC 2011&2012 Microblog Track. Results show that the model better overcome tweets' limited length shortage than traditional methods, good expansion terms are found and microblog retrieval performance are greatly improved by the scoring and ranking model.

关键词： Microblog Search model Term similarity graph Weighted scoring model Scoring Line graph retrieval TWITTER Scoring Hyperlinks

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A MANDARIN SPEECH recognition RESULT EVALUATION ALGORITHM ON MIXED WORDS

A MANDARIN SPEECH RECOGNITION RESULT EVALUATION ALGORITHM ON...

引用

2009 IEEE International Conference on Network Infrastructure and Digital Content(2009年IEEE网络基础设施与数字内容国际会议 IEEE IC-NIDC2009)

作者： Gang Liu Wei Chen Yujing Guo Jun Guo Pattern Recognition and Intelligent System Laboratory Beijing University of Posts and Telecommunications Beijing

ISBN: (纸本)9781424448999

Speech recognition result is always evaluated by dynamic programming algorithm which can find the best match between recognized results and references. And the match unit could be word, syllable, phone and so on. However, in mandarin speech recognition, this traditional algorithm is not accurate because of the unique characteristics of Chinese word-formation. In order to improve evaluation performance on Chinese, we proposed a mandarin speech recognition evaluation algorithm based on mixed words. Our experiments show that our proposed algorithm can effectively reduce the false error caused by traditional evaluation algorithm.

关键词： Speech recognition Result Evaluation Dynamic Programming Mized Words

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Efficient word-level sequential coding scheme of bit plane coding for EBCOT in JPEG2000

Efficient word-level sequential coding scheme of bit plane c...

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9th International Symposium on Consumer Electronics 2005, ISCE 2005

作者： Xiong, Cheng-Yi Tian, Jin-Wen Liu, Jian Institute of Pattern Recognition and Artificial Intelligence South-Center University for Nationalities Huazhong University of Science and Technology Wuhan China Key Laboratory of Education Ministry for Image Processing and Intelligent Control Institute of Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan China HUST

The embedded block coding with optimized truncation (EBCOT) is the state-of-the-art coding technique for image compression, which is the heart of the latest still image compression standard JPEG2000. EBCOT can be partitioned into three steps: bit plane coding (BPC), context adaptive binary arithmetic coding (CABAC) and postcompression rate-distortion (PCRD) optimization. The bit plane coding in JPEG2000 is a fractional bit-plane coding method, in which the transformed coefficients of a code block are coded bit plane by bit plane with 3 passes in each bit-plane, and context-decision (CX-D) pair of the coded symbol is generated for CABAC. In this paper, a new word-level sequential (WLS) coding scheme for BPC is presented, which makes all the passes coding be completed in one scan, with the context formation in all bit-planes being performed in parallel and all the samples being coded in sequential. The status variables used in context formation are produced on-the-fly. This new algorithm can efficiently implement both the regular mode and vertical causal one recommended by JPEG2000. The proposed algorithm reduces efficiently the size of memory and the amount of memory accessing, and increases significantly the speed of coding. It is well suited for both software and hardware implementation.1 © IEEE.

关键词： Image coding

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Geometric Numerical Integral Method in Compact Lie Group

Geometric Numerical Integral Method in Compact Lie Group

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6th International Conference on intelligent Computing and Signal Processing (ICSP)

作者： Chao Liu Shengyi Yang Key Laboratory of Pattern Recognition and Intelligent System of Guizhou Province Guizhou Minzu University Gui Yang China

ISBN: (纸本)9781665447300

Three dimensions special orthogonal group SO (3) is widely used to describe the rotation kinematics of the rigid body without local coordinates, which can avoid rotation singularity and unwinding in traditional methods. Propagating the rotation kinematics in SO (3) with a specific geometric integration method is not only to obtained numerical results with improved qualitative behavior, but also provided more accurate long-time integration results. While many studies have focused on geometric integration algorithms to preserve the geometric structure, this work has the additional objective of studying result accuracy. Integral curves on SO (3) obtained using the third-order Crouch-Grossman Lie group method are compared with numerical results using the third-order RKMK algorithms, the exponential coordinates method, and the simple projection method. Results show that the use of the Crouch-Grossman Lie group method better preserves the geometric structure of SO (3) for the larger time steps considered. It is also found that the third-order Crouch-Grossman algorithm is more accurate than the RKMK except for the smallest time step used.

关键词： Heuristic algorithms Signal processing algorithms Kinematics Signal processing

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Rapid disparity prediction for dynamic scenes

Rapid disparity prediction for dynamic scenes

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9th International Symposium on Advances in Visual Computing, ISVC 2013

作者： Jiang, Jun Cheng, Jun Chen, Baowen Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences China Chinese University of Hong Kong Hong Kong Hong Kong Shsenzhen Institute of Information Technology China Guangdong Provincial Key Laboratory of Robotics and Intelligent System China Shenzhen Key Laboratory of Computer Vision and Pattern Recognition China

ISBN: (纸本)9783642419133

Real-time 3D sensing plays a critical role in robotic navigation, video surveillance and human-computer interaction, etc. When computing 3D structures of dynamic scenes from stereo sequences, spatiotemporal stereo and scene flow methods can produce temporally coherent disparity. However, most existing methods do not utilize the previous disparity map sufficiently to compute the next disparity map, and the searching space of correspondences limits the speed of disparity computation for each image pair. This paper proposes an effective scheme to predict disparity maps from stereo sequences. In particular, we apply a robust 3D registration algorithm based on the angular-invariant feature to estimate the ego-motion of the stereo rig between consecutive frames, and present the transformation between consecutive disparity maps. The scheme can produce a sequence of temporally coherent disparity maps rapidly. We apply the new scheme to real outdoor scenes, and thorough empirical studies indicate the effectiveness of the new scheme for practical applications. © 2013 Springer-Verlag.

关键词： Human computer interaction

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3D model retrieval using density-based silhouette descriptor

3D model retrieval using density-based silhouette descriptor

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2nd International Conference on pattern recognition Applications and Methods, ICPRAM 2013

作者： Tang, Qi Yang, Xin Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Shanghai China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai 200240 China

ISBN: (纸本)9789898565419

In this paper we present a new content-based retrieval descriptor, density-based silhouette descriptor (DBS). It characterizes a 3D object with multivariate probability functions of its 2D silhouette features. The new descriptor is computationally efficient and induces a permutation property that guarantees invariance at the matching stage. Also, it is insensitive to small shape perturbations and mesh resolution. The retrieval performance on several 3D databases shows that the DBS provides state-of-art discrimination over a broad and heterogeneous set of shape categories.

关键词： Probability density function

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A KLD Based Method for Initial Set Selection in Active Learning

A KLD Based Method for Initial Set Selection in Active Learn...

引用

International Conference on Electronic Computer Technology

作者： Wei Chen Gang Liu Jun Guo Pattern Recognition and Intelligent System Laboratory Beijing University of Posts and Telecommunications Beijing China

ISBN: (纸本)9781424435623

Speech recognition systems are usually trained using tremendous transcribed samples, and training data preparation is intensively time-consuming and costly. Aiming at achieving better performance of acoustic model with less transcribed samples, active learning is used in acoustic model training. This learning scheme firstly selects and transcribes a small initial training set, then iteratively selects the most informative samples corresponding to a certain criterion from the unlabeled samples, then annotates them and adds the newly transcribed samples to the training set to update the acoustic model. Concerning that the initial set influences the performance and convergence rate of active learning a lot, we proposed a method for initial set selection based on Kullback-Leibler divergence (KLD). Our experiments show that active learning using initial set selected by our proposed method can achieve better performance.

关键词： Convergence Hidden Markov models pattern recognition Learning systems Telecommunication computing intelligent systems Laboratories Training data Speech recognition Databases

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Frequency warping based on two factor weighted fusion

Frequency warping based on two factor weighted fusion

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International Conference on systems and Informatics (ICSAI)

作者： Gang Liu Haobin Chen Ruchao Fan Pattern Recognition and Intelligent System Laboratory Beijing University of Posts and Telecommunications Beijing China

Traditional frequency warping algorithms in speech recognition mainly consider the spectrum offset caused by different vocal tract length. But in addition to the vocal tract length, the pronunciation diversity is also affected by the glottis difference. At the same time, the difference mentioned above is also interconnected. Although piecewise linear frequency warping considers the effect of the glottis and vocal tract, it will lose some information because it is not continuous and it only considers the effect of single factor. This paper proposes a two factor frequency warping algorithm based on the weighted fusion of the glottis resonant factor and the third formant factor. Compared with piecewise linear frequency warping, the method of spectrum aligned in this algorithm is smoother and takes the relationship between the glottis and vocal tract into account. Experimental results show that the recognition rate of the proposed algorithm is improved in the case of training data and testing data both matching and mismatching.

关键词： Resonant frequency Speech Speech recognition Physiology Semantics Feature extraction Acoustics

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Cross-Document Coreference Resolution Based on Automatic Text Summary

Cross-Document Coreference Resolution Based on Automatic Tex...

引用

International Workshop on Knowledge Discovery and Data Mining (WKDD)

作者： Sanyuan Gao Si Li Weiran Xu Jun Guo Pattern Recognition and Intelligent System Laboratory Beijing University of Posts and Telecommunications Beijing China

ISBN: (纸本)9781424453979

Cross-document coreference resolution plays an import part in the filed of natural language processing (NLP). It captures the ability of gathering documents for information about a certain entity. Most previous algorithms identify the underlying entity of a given document depending on the original text, which is unreliable if the original text contains multiple parts of different themes. In this paper, we propose a cross-document coreference resolution algorithm based on automatic text summary instead of the original text. In our approach, we extract query-specific and informative-indicative summary from the original text by using Hobbs algorithm and measure the similarity between two summaries. This automatic text summary-based cross-document coreference resolution (ATSCDCR) system is effective in disambiguating different entities of the same mention name and identifying the same entity of different mention names. The results from our experiments show that the macro average of ATSCDCR system is up to 73.16% and the micro average of ATSCDCR system is 67.34 %.

关键词： Data mining Joining processes pattern recognition intelligent systems Electronic mail Natural language processing Text recognition Testing Biomedical informatics Displays

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Feature Fusion of Speech Emotion recognition Based on Deep Learning

Feature Fusion of Speech Emotion Recognition Based on Deep L...

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IEEE International Conference on Network Infrastructure and Digital Content (IC-NIDC)

作者： Gang Liu Wei He Bicheng Jin Pattern Recognition and Intelligent System Laboratory Beijing University of Posts and Telecommunications Beijing China

Speech emotion recognition (SER) is a hot topic in academia. One of the key issues in improving the performance of SER systems is the choice of speech emotion features. In order to establish a robust speech emotion recognition system, it is essential to select the features which can be a perfect representation of speech emotion attributes. Researchers has done a lot of work, proposed a variety of emotional features and made great progress. Although each kind of features were proven to be effective, most of methods are based on a single type. In this paper, we proposed a method of feature fusion based on deep learning, combining spectral-based features and pitch-based hyper-prosodic features. The experiments show that this method improves the performance of speech emotion recognition system.

关键词： Feature extraction Emotion recognition Speech recognition Hidden Markov models Acoustics Data mining

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