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Candidate generation for interactive Chinese speech recognition

Candidate generation for interactive Chinese speech recognit...

引用

Joint Conferences on Pervasive computing (JCPC)

作者： Xinhui Li Xiangdong Wang Yueliang Qian Shouxun Lin Chinese Academy and Sciences Beijing China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy and Sciences Beijing China

ISBN: (纸本)9781424452279;9781424452286

Despite progress in automatic speech recognition, user involvement and assistance are still needed to achieve performance similar to human in real-world tasks. Though many interactive speech recognition systems using candidate selection are developed for English and Japanese, similar systems for Chinese face particular difficulties due to characteristics of the Chinese language, especially at the candidate generation stage. In this paper, a method is proposed for candidate generation in interactive Chinese speech recognition, which lists all competitive candidates in forms of Chinese characters in stead of words. The main idea is to align time-overlapped links in Chinese word lattice into clusters based on their phonetic similarity, and then obtain candidates by splitting words attached to links into Chinese characters. Experimental results demonstrated that the candidates generated by the proposed method can lead to high performance in interactive Chinese speech recognition.

关键词： Speech recognition Lattices Character generation Error correction Natural languages Humans Automatic speech recognition Laboratories Competitive intelligence information processing

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Detecting Unusual Pattern with Labeled Data in Two-Stage

Detecting Unusual Pattern with Labeled Data in Two-Stage

引用

International Conference on Fuzzy Systems and Knowledge Discovery (FSKD)

作者： Jincheng Li Qing He Zhongzhi Shi Chinese Academy of Sciences Beijing China The Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy and Sciences Beijing China

More analysis has been done to discover the meaningful unusual patterns which may mean fraud or anomaly. In this paper, a two-stage approach considering the labeled data's proposed to discover meaningful unusual observation, without the goal of classifying. We firstly apply hyper surface classification (HSC) algorithm to gain a separating hyper surface which includes several pieces. Observation in the sparse piece is viewed as the unusual pattern. For therpieces with local density, we construct a weighted graph for it and search the minimum spanning tree (MST), then detect further by cutting off several edges with the aximum weight. Combining the advantages of the two stages, a process of subdividing is proposed to consider the domain knowledge. Experimental results show that our approach can detect unusual pattern effectively together with other hidden valuable knowledge.

关键词： Pattern analysis Classification algorithms Credit cards Supervised learning Predictive models Fuzzy systems Laboratories information processing Computers information analysis

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Web Service Composition as Satisfiability Checking in Dynamic Description Logics

Web Service Composition as Satisfiability Checking in Dynami...

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International Conference on Grid and Cooperative computing (GCC)

作者： Limin Chen Hong Hu Zhongzhi Shi Chinese Academy and Sciences Beijing China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy and Sciences Beijing China

The automation of Web service composition (WSC) has emerged as a major research topic since an ever-increasing number of Web services are created and published, which make manually analyzing them and creating the desired composite service difficult, or even beyond human abilities. This paper presented an approach for the automation of WSC at the functional level based on dynamic description logics (DDLs), extensions of description logics (DLs) with a dynamic dimension. By embracing knowledge in actions into DLs, DDLs couple the static information provided by ontologies and the dynamic processing provided by Web services, and offer a uniform way to represent and reason about both static and dynamic aspects of the Web content. Our approach employed classical DL-TBoxes to capture the constraints of the domain, DL-ABoxes to describe the states, and DL-formulas to encode the client requirements respectively. Actions in DDLs were used to abstract the functionalities of the existing Web services which were classified into categories in terms of their functionalities. In such a way, the WSC was reduced to formula satisfiability and solved by a decidable tableau procedure. We also implemented a reasoning engine based on the dynamic description logic D-ALCHOQ, and tested our approach on a simple variation of the travel scenario; the preliminary results certified the potential of the approach.

关键词： Web services Automation information processing Computers Humans Logic testing Logic design Grid computing Ontologies Engines

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Advertisement evaluation using visual saliency based on foveated image

Advertisement evaluation using visual saliency based on fove...

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IEEE International Conference on Multimedia and Expo (ICME)

作者： Zhiguo Ma Laiyun Qing Jun Miao Xilin Chen Chinese Academy and Sciences Beijing China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy and Sciences Beijing China

This paper proposes a novel approach to advertisement evaluation using automatic salient regions. The salient regions are detected using a predicting model, in which the estimation are obtained by the space variant foveated image. The saliency is defined as the difference between the input image and its estimation. Then an advertisement is determined as attractive if the detected salient regions are overlapped with the interested regions of the advertisement. The experimental results on the advertisements data set are encouraging.

关键词： Computational modeling Humans Eyes Psychology Laboratories Computational intelligence information processing Computers Layout Machine learning

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Exploring Web Resources in Social Annotation Services in Hierarchy

Exploring Web Resources in Social Annotation Services in Hie...

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International Conference on Grid and Cooperative computing (GCC)

作者： Kun Yang Zhongzhi Shi Chinese Academy and Sciences Beijing China The Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy and Sciences Beijing China

This paper considers the problem of the organizing way of Web resources in social annotation systems. Currently, the Web resources in social annotation systems contain multiple topics, organizing them into different semantic clusters will facilitate userspsila browsing and search greatly. This paper proposes a hierarchy clustering method to organize Web resources in hierarchy by making full use of the linkage relationship between the Web resources and their annotations. In this way, users can browse or search a Web resource collection in a Google mappsilas way by going deep into a collection with more details. Some experiments on data set from *** are performed to justify the effectiveness of our method and a prototype based on pictures in Flickr is developed to demonstrate our idea.

关键词： Laboratories information processing Computers Organizing Grid computing Clustering methods Couplings Prototypes Clustering algorithms YouTube

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A novel Hebbian rules based method for computation of sparse coding basis vectors

A novel Hebbian rules based method for computation of sparse...

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5th International Conference on Natural Computation, ICNC 2009

作者： Zou, Baixian Miao, Jun Yang, Xiaoling Duan, Lijuan Qiao, Yuanhua Department of Information Science and Technology College of Arts and Science of Beijing Union University Beijing 100083 China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China Tianjin Academy of Agricultural Science Tianjin 300192 China College of Computer Science and Technology Beijing University of Technology Beijing 100022 China College of Applied Science Beijing University of Technology Beijing 100022 China

ISBN: (纸本)9780769537368

Sparse coding has high-performance encoding and ability to express images, sparse encoding basis vector plays a crucial role. The computational complexity of the most existing sparse coding basis vectors of is relatively large. In order to reduce the computational complexity and save the time to train basis vectors. A new Hebbian rules based method for computation of sparse coding basis vectors is proposed in this paper. A two-layer neural network is constructed to implement the task. The main idea of our work is to learn basis vectors by removing the redundancy of all initial vectors using Hebbian rules. The experiments on natural images prove that the proposed method is effective for sparse coding basis learning. It has the smaller computational complexity compared with the previous work. © 2009 IEEE.

关键词： Computational complexity

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Three-dimensional source reconstruction for bioluminescence tomography using the LSQR method with preconditioning

Three-dimensional source reconstruction for bioluminescence ...

引用

MIPPR 2009 - Medical Imaging, Parallel processing of Images, and Optimization Techniques: 6th International Symposium on Multispectral Image processing and Pattern Recognition

作者： Yu, Jingjing Liu, Fang Jiao, Licheng He, Xiaowei School of Computer Science and Technology Xidian University Xi'an 710071 China Scholl of Physics and Information Technology Shaanxi Normal University Xi'an 710062 China Key Laboratory of Intelligent Perception and Image Understanding Ministry of Education of China Xi'an 710071 China Institute of Intelligent Information Processing Xidian University Xi'an 710071 China School of Information Science and Technology Northwest University Xi'an 710069 China

ISBN: (纸本)9780819478085

As a novel optical molecular imaging modality, Bioluminescence Tomography (BLT) aims at quantitative reconstruction of the bioluminescent source distribution inside the biological tissue from the optical signals measured on the living animal surface, which is a highly ill-posed inverse problem. In this paper, with the finite element method solving the diffusion equation, an iterative regularization algorithm, referred to as least square QR-factorization (LSQR), is applied to the inverse problem in BLT. The affect of the preconditioning strategy on the LSQR method (PLSQR) for BLT is also investigated. The Simulations with a heterogeneous mouse chest phantom demonstrate that by incorporating a priori knowledge of the permissible source region, the LSQR method can reconstruct the source accurately and stably. Moreover, by employing preconditioning strategy, PLSQR outperforms LSQR in terms of source power density and convergence speed. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Inverse problems

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Learning image semantics with latent aspect model

Learning image semantics with latent aspect model

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IEEE International Conference on Multimedia and Expo (ICME)

作者： Zhixin Li Xi Liu Zhiping Shi Zhongzhi Shi Chinese Academy of Sciences Beijing Beijing CN The Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy and Sciences Beijing China

Automatic image annotation has become an important and challenging problem due to the existence of semantic gap. In this paper, we present an approach based on probabilistic latent semantic analysis (PLSA) to accomplish the tasks of semantic image annotation and retrieval. In order to model training images precisely, we employ two PLSA models to capture semantic information from visual and textual modalities respectively. Then an adaptive asymmetric learning approach is proposed to fuse aspects which are learned from both modalities. For each image document, the weight of each modality is determined by its contribution to the content of the image. Consequently, the two models are linked with the same distribution over aspects. This structure can predict semantic annotation for an unseen image because it associates visual and textual modalities properly. Finally, we compare our approach with several previous approaches on a standard Corel dataset. The experiment results show that our approach performs more effective and accurate.

关键词： Image retrieval Image databases Fuses Indexing Feature extraction Spatial databases Visual databases Hidden Markov models Laboratories information processing

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Skeleton-based fast path planning for UAV

Skeleton-based fast path planning for UAV

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MIPPR 2009 - Remote Sensing and GIS Data processing and Other Applications: 6th International Symposium on Multispectral Image processing and Pattern Recognition

作者： Liu, Xin Zhou, Chengping Ding, Mingyue Cai, Chao Institute for Pattern Recognition and Artificial Intelligence National Lab. for Multi-spectral Information Processing Technologies Huazhong University of Science and Technology Wuhan 430074 China College of Life Science and Technology Image Processing and Intelligent Control Key Laboratory of Education Ministry of China Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9780819478092

A new path planning method for UAV in static workspace is presented. The method can find a nearly optimal path in short time which satisfies the UAV kinematic constraints. The method makes use of the skeletons to construct the graph of the planning space considering the configuration of the obstacles and utilizes the graph to find a shortest collision-free path, and a novel technique is utilized to convert the free path into a feasible path. The method can be applied to different applications and easy to be implemented. Experimental results showed that the path planning can be done in a fraction of second on a contemporary workstation (2-3 seconds) under the condition of satisfying the kinematic constraints. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Motion planning

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A Comparative Study of PCA, LDA and Kernel LDA for Image Classification

A Comparative Study of PCA, LDA and Kernel LDA for Image Cla...

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International Symposium on Ubiquitous Virtual Reality, ISUVR

作者： Fei Ye Zhiping Shi Zhongzhi Shi Chinese Academy of Sciences Beijing Beijing CN Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy and Sciences Beijing China

Although various discriminant analysis approaches have been used in content-based image retrieval (CBIR) application, there have been relatively few concerns with kernel-based methods. Furthermore, these CBIR applications still applied discriminant analysis to face images as face recognition did. In this paper we concerns images with general semantic concepts. We use our presented symmetrical invariant LBP (SILBP) texture descriptor to extract image visual features. We then explored effectiveness of principal component analysis (PCA), fisher linear discriminant analysis (LDA), and kernel LDA algorithms in providing optimal discrimination features. Following it, we present an LDA based framework to carry out kernel discrimiant analysis in our application. By taking advantage of the efficiency in nonlinear condition of kernel-based methods and the simplicity of LDA, the proposed approach can improve the retrieval precision of CBIR. The experimental results validate the effectiveness of the proposed approach.

关键词： Linear discriminant analysis Principal component analysis Kernel Image classification Image analysis information retrieval Image retrieval Content based retrieval Face recognition Feature extraction

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