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检索条件"机构=Key Laboratory of Intelligent Information Perception and Processing Technology"

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SPEAKER AGE RECOGNITION BASED ON ISOLATED WORDS BY USING SVM

SPEAKER AGE RECOGNITION BASED ON ISOLATED WORDS BY USING SVM

引用

2014 IEEE 3rd International Conference on Cloud Computing and Intelligence Systems

作者： Mengdi Yue Ling Chen Jie Zhang Hong Liu School of Electronic and Information Engineering University of Science and Technology Engineering Lab on Intelligent Perception for Internet of Things(ELIP) Shenzhen Graduate School of Peking University Engineering Lab on Intelligent Perception for Internet of Things(ELIP) The Key Laboratory of Machine PerceptionPeking University

Speaker age recognition is an essential technique in automation speech recognition based on the speech wavform parameters in speaker's ***,there are several challenges in speaker age recognition,such as innate differences in speaker's voice,subjective classification fuzzy,*** issue of speaker age based on isolated words is proposed in this paper,including support vector machine(SVM),picking up Mel frequency cepstrum coefficient(MFCC) characteristics of isolated words to distinguish the speaker's *** voicebox of this paper includes 4507 isolated word *** results show that the recognition rate based on isolated word speech can reach 72.93%.Through the experiment towards SVM classifier,we could find that the performance is improved without normalization for MFCC.

关键词： Isolated words Mel frequency cepstrum coefficients Age recognition Support vector machine

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Hierarchical multi-feature fusion for multimodal data analysis

Hierarchical multi-feature fusion for multimodal data analys...

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作者： Zhang, Hong Chen, Li Liu, Jun Yuan, Junsong College of Computer Science and Technology Wuhan University of Science and Technology Wuhan China Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System China Institute for Media Innovation Nanyang Technological University Singapore Singapore School of EEE Nanyang Technological University Singapore Singapore

ISBN: (纸本)9781479957514

Multimedia data is usually represented with different low-level features, and different types of multimedia data, namely multimodal data, often coexist in many data sources. It is interesting and challenging to learn comprehensive semantics from multiple low-level features for multimodal data analysis. In this paper, we propose a new algorithm, namely hierarchical multi-feature fusion for multimodal data semantics understanding. Our approach explores intra-modality structural information derived from each type of feature, and further proposes transductive inter-modality fusion strategy, which analyzes canonical correlation between different modalities. Extensive experiments are conducted on collected multimodal database for data classification application. The experiment results show that the performance of our algorithm is remarkable and demonstrate its superiority over several existing algorithms. © 2014 IEEE.

关键词： Semantics

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Positional translation language model for ad-hoc information retrieval

Positional translation language model for ad-hoc information...

引用

18th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2014

作者： Tu, Xinhui Luo, Jing Li, Bo He, Tingting Gu, Jinguang College of Computer Science and Technology Wuhan University of Science and Technology Wuhan China Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan China Department of Computer Science Central China Normal University Wuhan China State Key Lab. of Software Engineering Wuhan University Wuhan China

ISBN: (纸本)9783319066042

Most existing language modeling approaches are based on the term independence hypothesis. To go beyond this assumption, two main directions were investigated. The first one considers the use of the proximity features that capture the degree to which search terms appear close to each other in a document. Another one considers the use of semantic relationships between words. Previous studies have proven that these two types of information, including term proximity features and semantic relationships between words, are both useful to improve retrieval performance. Intuitionally, we can use them in combination to further improve retrieval performance. Based on this idea, this paper propose a positional translation language model to explicitly incorporate both of these two types of information under language modeling framework in a unified way. In the first step, we present a proximity-based method to estimate word-word translation probabilities. Then, we define a translation document model for each position of a document and use these document models to score the document. Experimental results on standard TREC collections show that the proposed model achieves significant improvements over the state-of-the-art models, including positional language model, and translation language models. © 2014 Springer International Publishing.

关键词： information retrieval

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Twin Support Vector Machines Based on the Mixed Kernel Function

Twin Support Vector Machines Based on the Mixed Kernel Funct...

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The 6th International Conference on Computer Research and Development

作者： Fulin Wu Shifei Ding School of Computer Science and Technology China University of Mining and Technology Key Laboratory of Intelligent Information Processing Institute of Computing TechnologyChinese Academy of Sciences

The efficiency and performance of the Twin Support Vector Machines(TWSVM) are better than the traditional support vector machines when it deals with the problems. However, it also has the problem of selecting kernel functions. Generally, TWSVM selects the Gaussian radial basis kernel function. Although it has a strong learning ability, its generalization ability is relatively weak. In a certain extent, this will limit the performance of TWSVM. In order to solve the problem of selecting kernel functions in TWSVM, we propose the twin support vector machines based on the mixed kernel function(MK-TWSVM) in this paper. To make full use of the learning ability of local kernel functions and the excellent generalization ability of global kernel functions, MK-TWSVM selects a global kernel function and a local kernel function to construct a mixed kernel function which has the better performance. The experimental results indicate that the mixed kernel function makes TWSVM have the good learning ability and generalization ability. So it improves the performance of TWSVM.

关键词： mixed kernel function TWSVM kernel function

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Prediction of hot regions in protein-protein interaction based on the Gi statistics and cascade classifier

Prediction of hot regions in protein-protein interaction bas...

引用

IEEE International Conference on Bioinformatics and Biomedicine

作者： Bingqin Tan Xiaolong Zhang Hubei Key Laboratory of Intelligent Information Processing and Real-time Industrial System School of Computer Science and Technology Wuhan University of Science and Technology

ISBN: (纸本)9781479956708

There is an important relationship between the stability of protein complex and hot region. Research has shown that in protein-protein interaction (PPI), residues are denser around the hot region. Therefore, this paper proposed an algorithm based on Gi statistics, regional division rule and regional amplification principle to form residue dense region (RDR);Then, according to the results of cascade classifier composed of Naive Bayes and Back-Propagation (BP) neural network classifier, non-hotspot residues in RDRs were removed;At length, we used binding free energy change value calculated from Robetta Server to modify predicted hot regions. The experimental results showd that the proposed method can effectively improve the prediction accuracy on hot regions.

关键词： Protein-protein interaction Hot region Gi statistics Cascade classifier Robatta

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Laminated paper counting algorithm based on compressive sensing and hough transform

Laminated paper counting algorithm based on compressive sens...

引用

International Conference on information technology and Electronic Commerce

作者： Hui Wang Dongfang Chen Xiaofeng Wang College of Computer Science and Technology Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan China

ISBN: (纸本)9781479953004

According to the problem that conventional laminated paper counting algorithms have some unavoidable shortcomings such as high dependence on the quality of laminated paper and noise sensitivity, we propose a laminated paper counting algorithm based on compressive sensing (CS) and Hough transform (HT). In the proposed algorithm, the over-complete dictionary which is created by dispersing the Hough transform space of straight lines acts as the sparse matrix. Making use of high degree of sparse nature of the laminated paper image, we can obtain the accurate result through using CS theory. Experimental results on simulation images and laminated paper images have shown that our proposed algorithm can effectively restrain noise of the laminated paper image, and will get accurate experimental results with fewer CS measurements.

关键词： Transforms Image reconstruction Sparse matrices Matching pursuit algorithms Image coding Signal to noise ratio

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AN ONLINE LEARNED HOUGH FOREST MODEL FOR MULTI-TARGET TRACKING

AN ONLINE LEARNED HOUGH FOREST MODEL FOR MULTI-TARGET TRACKI...

引用

IEEE International Conference on Image processing

作者： Jun Xiang Nong Sang Jianhua Hou National Key Laboratory of Science and Technology on Multispectral Information Processing School of Automation Huazhong University of Science and Technology Hubei Key Laboratory of Intelligent Wireless Communications South-central University for nationalities

ISBN: (纸本)9781479957521

We present an online learned framework for multiple target tracking in a crowded scene. The tracking problem is formulated as a detection-based progressive association task. Firstly, reliable tracklets are generated by low level constraints among detection responses. Then longer tracklets associations are generated based on online learned Hough forest framework which effectively combines motion and appearance information for discrimination between two tracklets. In online learning scene, the association is formulated as a MAP problem and training examples are collected based on spatial-temporal constraints. In order to alleviate the drifting problem of online learning, Hungarian algorithm is employed to modify associated errors and update the training set. The experimental results show the effectiveness of our approach.

关键词： Multi-Target Tracking Online learned Hough forest

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Admissible Rate Region for Network Encoding of Independent information Sources

Admissible Rate Region for Network Encoding of Independent I...

引用

International Conference on Computer Modeling and Simulation, UKSIM

作者： Zhifang Wu Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System College of Computer Science and Technology Wuhan University of Science and Technology

ISBN: (纸本)9781479949212

Network coding (NC) is one of the promising techniques to improve network throughput towards the Shannon limit. NC has been proven to be able to achieve the max-flow min-cut bound for single source multicast networks. For multi-information-source multicast networks, however, the question of how to use NC is still to be answered. In this paper we will focus on the simple case of multi-information-source independent network encoding. The region of admissible rate set of this case will be provided. With this rate region obtained, more advanced network encoding algorithms for multi-information source multicast networks can be further developed.

关键词： Network coding Channel coding Decoding Polynomials Joints Receivers

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3D Action Recognition Based on Limb Angle Model

3D Action Recognition Based on Limb Angle Model

引用

2014 4th IEEE International Conference on information Science and technology

作者： Jing Du Dongfang Chen College of Computer Science and Technology Wuhan University of Science and Technology Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System

Human action recognition technology has been applied to intelligent security surveillance, content-based image and video retrieval and natural user interface. How to make use of the new type of data, 3D skeleton joint position extracted by 3D depth camera, has been a highly active research topic. A posture representation model is proposed, which is invariant to limb length, length ratio between body parts and body orientation. This model contains polar angle and azimuthal angle of each limb in the spherical coordinate system which is established by the features of body joints. Hidden Markov Model（HMM） is exploited for recognition. Skeleton sequences of different body orientation are collected as experimental data. Experimental results demonstrate the effectiveness of our approach.

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Decoding overlapped time division multiplexing system with Fano algorithm

Decoding overlapped time division multiplexing system with F...

引用

10th International Conference on Wireless Communications, Networking and Mobile Computing (WiCOM 2014)

作者： Qingshuang Zhang Ke Wang Aijun Liu Daoben Li Xiaofei Pan School of Communications Engineering PLA University of Science and Technology Nanjing China School of Information and Engineering Key Laboratory of Information Processing and Intelligent Technology Beijing University of Posts and Telecommunications China

ISBN: (纸本)9781510804166

OvTDM is a new transmission scheme that can obtain high spectral efficiency with very low threshold signal noise ratio (SNR) by using the inter symbol interference (ISI). Fano algorithm (FA) is researched in this paper to implement fast ML decoding at high spectral efficiency for OvTDM. Numerical results show that the complexity of OvTDM with FA has no relationship with the number of state which is lower than 15% of that of Viterbi algorithm and the bit SNR loss is under 2 dB. Moreover, OvTDM with FA can even outperform Shannon limit when spectral is above 6.7 bits/s/Hz.

关键词： FA ISI MLSD OvTDM maximum likelihood sequence detection Fano algorithm spectral efficiency FAS gene signal to noise ratios ISIS SATELLITES Shannon limit Time division time division multiplexing Viterbi algorithm DECODING

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