11,901 research outputs found

    Fast and Accurate OOV Decoder on High-Level Features

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    This work proposes a novel approach to out-of-vocabulary (OOV) keyword search (KWS) task. The proposed approach is based on using high-level features from an automatic speech recognition (ASR) system, so called phoneme posterior based (PPB) features, for decoding. These features are obtained by calculating time-dependent phoneme posterior probabilities from word lattices, followed by their smoothing. For the PPB features we developed a special novel very fast, simple and efficient OOV decoder. Experimental results are presented on the Georgian language from the IARPA Babel Program, which was the test language in the OpenKWS 2016 evaluation campaign. The results show that in terms of maximum term weighted value (MTWV) metric and computational speed, for single ASR systems, the proposed approach significantly outperforms the state-of-the-art approach based on using in-vocabulary proxies for OOV keywords in the indexed database. The comparison of the two OOV KWS approaches on the fusion results of the nine different ASR systems demonstrates that the proposed OOV decoder outperforms the proxy-based approach in terms of MTWV metric given the comparable processing speed. Other important advantages of the OOV decoder include extremely low memory consumption and simplicity of its implementation and parameter optimization.Comment: Interspeech 2017, August 2017, Stockholm, Sweden. 201

    Semantic annotation, publication, and discovery of Java software components: an integrated approach

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    Component-based software development has matured into standard practice in software engineering. Among the advantages of reusing software modules are lower costs, faster development, more manageable code, increased productivity, and improved software quality. As the number of available software components has grown, so has the need for effective component search and retrieval. Traditional search approaches, such as keyword matching, have proved ineffective when applied to software components. Applying a semantically- enhanced approach to component classification, publication, and discovery can greatly increase the efficiency of searching and retrieving software components. This has been already applied in the context of Web technologies, and Web services in particular, in the frame of Semantic Web Services research. This paper examines the similarities between software components and Web services and adapts an existing Semantic Web Service publication and discovery solution into a software component annotation and discovery tool which is implemented as an Eclipse plug-in

    U.S. Patent Literature Survey of Agrobacterium-Mediated Transformation of Sweet Potato (Ipomoea Batatas)

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    A team of researchers and patent information scientists at Franklin Pierce Law Center were asked to evaluate the patent and literature landscape related to the Agrobacterium-mediated transformation in sweet potato with respect to the U.S. patents and patent applications. This report provides a patent landscape of the Agrobacterium-mediated transformation of sweet potato. The report includes the applicable methods of transformation and has also included certain patents and patent applications which claim a transformed plant by virtue of these methods. In certain cases, the claim structure covers Agrobacterium-mediated transformation technology via system and composition of matter claims and not the more prevalent method claims. Sweet potato plant (Ipomoea batatas) is adaptable to a broad range of agroecological conditions and fits in low input agriculture. It is highly productive even under adverse farming conditions. Sweet potato is grown in more than 100 countries as a valuable source of food, animal feed and industrial raw material. It is a staple crop in many South East Asian and African countries. Traditional plant breeding has contributed to the improvement of sweet potato, especially in developed countries such as the U.S.A. and Japan. Because of the biological complexities of sweet potato, sexual hybridization strategies have not been very effective in developing improved cultivars. Confidential Therefore, biotechnological tools, such as gene transfer, are very attractive in sweet potato improvement, as they enable direct introduction of desirable genes from other sources into preadapted cultivars

    Ontology-based specific and exhaustive user profiles for constraint information fusion for multi-agents

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    Intelligent agents are an advanced technology utilized in Web Intelligence. When searching information from a distributed Web environment, information is retrieved by multi-agents on the client site and fused on the broker site. The current information fusion techniques rely on cooperation of agents to provide statistics. Such techniques are computationally expensive and unrealistic in the real world. In this paper, we introduce a model that uses a world ontology constructed from the Dewey Decimal Classification to acquire user profiles. By search using specific and exhaustive user profiles, information fusion techniques no longer rely on the statistics provided by agents. The model has been successfully evaluated using the large INEX data set simulating the distributed Web environment

    Web Service Discovery in the FUSION Semantic Registry

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    The UDDI specification was developed as an attempt to address the key challenge of effective Web service discovery and has become a widely adopted standard. However, the text-based indexing and search mechanism that UDDI registries offer does not suffice for expressing unambiguous and semantically rich representations of service capabilities, and cannot support the logic-based inference capacity required for facilitating automated service matchmaking. This paper provides an overview of the approach put forward in the FUSION project for overcoming this important limitation. Our solution combines SAWSDL-based service descriptions with service capability profiling based on OWL-DL, and automated matchmaking through DL reasoning in a semantically extended UDDI registry

    Reverse spatial visual top-k query

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    With the wide application of mobile Internet techniques an location-based services (LBS), massive multimedia data with geo-tags has been generated and collected. In this paper, we investigate a novel type of spatial query problem, named reverse spatial visual top- kk query (RSVQ k ) that aims to retrieve a set of geo-images that have the query as one of the most relevant geo-images in both geographical proximity and visual similarity. Existing approaches for reverse top- kk queries are not suitable to address this problem because they cannot effectively process unstructured data, such as image. To this end, firstly we propose the definition of RSVQ k problem and introduce the similarity measurement. A novel hybrid index, named VR 2 -Tree is designed, which is a combination of visual representation of geo-image and R-Tree. Besides, an extension of VR 2 -Tree, called CVR 2 -Tree is introduced and then we discuss the calculation of lower/upper bound, and then propose the optimization technique via CVR 2 -Tree for further pruning. In addition, a search algorithm named RSVQ k algorithm is developed to support the efficient RSVQ k query. Comprehensive experiments are conducted on four geo-image datasets, and the results illustrate that our approach can address the RSVQ k problem effectively and efficiently
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