Dublin City University at CLEF 2007: Cross-Language Speech Retrieval Experiments

The Dublin City University participation in the CLEF 2007 CL-SR English task concentrated primarily on issues of topic translation. Our retrieval system used the BM25F model and pseudo relevance feedback. Topics were translated into English using the Yahoo! BabelFish free online service combined with domain-specific translation lexicons gathered automatically from Wikipedia. We explored alternative topic translation methods using these resources. Our results indicate that extending machine translation tools using automatically generated domainspecific translation lexicons can provide improved CLIR effectiveness for this task

ICT-DCU question answering task at NTCIR-6

This paper describes details of our participation in the NTCIR-6 Chinese-to-Chinese Question Answering task. We use the “retrieval plus extraction approach” to get answers for questions. We first split the documents into short passages, and then retrieve potentially relevant passages for a question, and finally extract named entity answers from the most relevant passages. For question type identification, we use simple heuristic rules which cover most questions. The Lemur toolkit was used with the okapi model for document retrieval. Results of our task submission are given and some preliminary conclusions drawn

Shaping of molecular weight distribution using b-spline based predictive probability density function control

Issues of modelling and control of molecular weight distributions (MWDs) of polymerization products have been studied under the recently developed framework of stochastic distribution control, where the purpose is to design the required control inputs that can effectively shape the output probability density functions (PDFs) of the dynamic stochastic systems. The B-spline Neural Network has been implemented to approximate the function of MWDs provided by the mechanism model, based on which a new predictive PDF control strategy has been developed. A simulation study of MWD control of a pilot-plant styrene polymerization process has been given to demonstrate the effectiveness of the algorithms

Mechanical performance and fracture behavior of Fe₄₁Co₇Cr₁₅Mo₁₄Y₂C₁₅B₆ bulk metallic glass

The mechanical properties of a new Fe₄₁Co₇Cr₁₅Mo₁₄Y₂C₁₅B₆ bulk glassy alloy were studied by impact bending, compression, and hardness tests carried out at room temperature. The compressive fracture strength, elastic strain to fracture, Young’s modulus and Vickers hardness were measured to be 3.5 GPa, 1.5%, 265 GPa, and 1253 kg mm⁻², respectively. The fracture mode of the glassy alloy under uniaxial compression is different from those of other bulk metallic glasses in that this fracture mode causes the samples to be broken, in an exploding manner, into a large number of micrometer-scale pieces. The fracture mechanisms of this bulk glassy alloy under bending and uniaxial compression are discussed based on the observation of the fracture surfaces. Vickers indentation tests indicate that the structure of the glassy ingot may be inhomogeneous

A 16-channel Digital TDC Chip with internal buffering and selective readout for the DIRC Cherenkov counter of the BABAR experiment

A 16-channel digital TDC chip has been built for the DIRC Cherenkov counter of the BaBar experiment at the SLAC B-factory (Stanford, USA). The binning is 0.5 ns, the conversion time 32 ns and the full-scale 32 mus. The data driven architecture integrates channel buffering and selective readout of data falling within a programmable time window. The time measuring scale is constantly locked to the phase of the (external) clock. The linearity is better than 80 ps rms. The dead time loss is less than 0.1% for incoherent random input at a rate of 100 khz on each channel. At such a rate the power dissipation is less than 100 mw. The die size is 36 mm2.Comment: Latex, 18 pages, 13 figures (14 .eps files), submitted to NIM

Multivariate Nonnegative Quadratic Mappings

In this paper we study several issues related to the characterization of speci c classes of multivariate quadratic mappings that are nonnegative over a given domain, with nonnegativity de ned by a pre-speci ed conic order.In particular, we consider the set (cone) of nonnegative quadratic mappings de ned with respect to the positive semide nite matrix cone, and study when it can be represented by linear matrix inequalities.We also discuss the applications of the results in robust optimization, especially the robust quadratic matrix inequalities and the robust linear programming models.In the latter application the implementational errors of the solution is taken into account, and the problem is formulated as a semide nite program.optimization;linear programming;models

Examining the contributions of automatic speech transcriptions and metadata sources for searching spontaneous conversational speech

The searching spontaneous speech can be enhanced by combining automatic speech transcriptions with semantically related metadata. An important question is what can be expected from search of such transcriptions and different sources of related metadata in terms of retrieval effectiveness. The Cross-Language Speech Retrieval (CL-SR) track at recent CLEF workshops provides a spontaneous speech test collection with manual and automatically derived metadata fields. Using this collection we investigate the comparative search effectiveness of individual fields comprising automated transcriptions and the available metadata. A further important question is how transcriptions and metadata should be combined for the greatest benefit to search accuracy. We compare simple field merging of individual fields with the extended BM25 model for weighted field combination (BM25F). Results indicate that BM25F can produce improved search accuracy, but that it is currently important to set its parameters suitably using a suitable training set

Multilingual search for cultural heritage archives via combining multiple translation resources

The linguistic features of material in Cultural Heritage (CH) archives may be in various languages requiring a facility for effective multilingual search. The specialised language often associated with CH content introduces problems for automatic translation to support search applications. The MultiMatch project is focused on enabling users to interact with CH content across different media types and languages. We present results from a MultiMatch study exploring various translation techniques for the CH domain. Our experiments examine translation techniques for the English language CLEF 2006 Cross-Language Speech Retrieval (CL-SR) task using Spanish, French and German queries. Results compare effectiveness of our query translation against a monolingual baseline and show improvement when combining a domain-specific translation lexicon with a standard machine translation system

Domain-specific query translation for multilingual access to digital libraries

Accurate high-coverage translation is a vital component of reliable cross language information access (CLIR) systems. This is particularly true of access to archives such as Digital Libraries which are often specific to certain domains. While general machine translation (MT) has been shown to be effective for CLIR tasks in information retrieval evaluation workshops, it is not well suited to specialized tasks where domain specific translations are required. We demonstrate that effective query translation in the domain of cultural heritage (CH) can be achieved by augmenting a standard MT system with domain-specific phrase dictionaries automatically mined from the online Wikipedia. Experiments using our hybrid translation system with sample query logs from users of CH websites demonstrate a large improvement in the accuracy of domain specific phrase detection and translation

A semantic event detection approach for soccer video based on perception concepts and finite state machines

A significant application area for automated video analysis technology is the generation of personalized highlights of sports events. Sports games are always composed of a range of significant events. Automatically detecting these events in a sports video can enable users to interactively select their own highlights. In this paper we propose a semantic event detection approach based on Perception Concepts and Finite State Machines to automatically detect significant events within soccer video. Firstly we define a Perception Concept set for soccer videos based on identifiable feature elements within a soccer video. Secondly we design PC-FSM models to describe semantic events in soccer videos. A particular strength of this approach is that users are able to design their own semantic events and transfer event detection into graph matching. Experimental results based on recorded soccer broadcasts are used to illustrate the potential of this approach