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This paper describes methods for evaluating automatic speech recognition (ASR) systems in comparison with human perception results, using measures derived from linguistic distinctive features. Error patterns in terms of manner, place and voicing are presented, along with an examination of confusion matrices via a distinctive-feature-distance metric. These evaluation methods contrast with conventional...
Big data revolution has created an unprecedented demand for intelligent data management solutions on a large scale. While data management has traditionally been used as a synonym for relational data processing, in recent years a new group popularly known as NoSQL databases have emerged as a competitive alternative. There is a pressing need to gain greater understanding of the characteristics of modern...
Performance of modern day computer systems greatly depends on the wide range of workloads, which run on the systems. Thus, a representative set of workloads, representing the different classes of real-world applications, need to be used by computer designers and researchers for processor design-space evaluation studies. While a number of different benchmark suites are available, a few common benchmark...
Owing to the thriving market of stereoscopic image based applications, efficient and effective 3D image quality assessment (IQA) techniques become colossally required these days. Consequently, we introduce a new reduced-reference (RR) stereoscopic image quality metric to meet this demand, through measuring Structural degradation and Saliency based Parallax compensation Model (SSPM). Experimental results...
With the rapid growth in video-based services, and as users are becoming increasingly quality-aware, the reliable estimation of video quality has become extremely important. While a multitude of objective Video Quality Assessment (VQA) metrics with various performance and complexity have been proposed, the nonlinearity of video quality and the lack of clear interpretations of the metrics make difficult...
A current challenge in computing centers with different clusters to run applications is which multicore systems must we choose to run a given shared-memory parallel application. Our proposal is to generate a node performance profile database (NPPDB), composed by performance profiles given by distinct micro benchmark-target node combination. Then, applications are executed on a base node to identify...
Research in computer science evolves very quickly. In order to prove the efficiency of a new algorithm, it is generally necessary to show some results on a large and significant benchmark used in the state of the art. This fact has for consequence the need of a large computation capability in a research laboratory. We address in this paper the performance evaluation of biometric systems through distributed...
Convergence of data mining and process management is ideal - but still limited. An example of such a convergence is presented in the form of APE Framework that addresses the problem of static-agent-assignment-strategies in Workflow Management Systems (WfMS) - one cause of poor business process performance since all eligible agents may be assigned to a task instead of only assigning those which are...
Performance regression testing detects performance regressions in a system under load. Such regressions refer to situations where software performance degrades compared to previous releases, although the new version behaves correctly. In current practice, performance analysts must manually analyze performance regression testing data to uncover performance regressions. This process is both time-consuming...
We present a performance evaluation of interest dissemination in Haggle. Haggle is a data-centric, searchable, network architecture for opportunistic communication. In a data-centric network the driving force for information delivery is the interests in a particular data and other nodes' knowledge about those interests. This paper presents how interests and data are represented and distributed in...
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