Minimum error rate training (MERT) involves choosing parameter values for a machine translation (MT) system that maximize performance on a tuning set as measured by an automatic evaluation metric, such as BLEU. The method is best when the system will eventually be evaluated using the same metric, but in reality, most MT evaluations have a human-based component. Although performing MERT with a h...

In this paper, we describe our submission to WMT 2015 Tuning Task. We integrate a dependency-based MT evaluation metric, RED, to Moses and compare it with BLEU and METEOR in conjunction with two tuning methods: MERT and MIRA. Experiments are conducted using hierarchical phrase-based models on Czech–English and English–Czech tasks. Our results show that MIRA performs better than MERT in most cas...

ORIGAMI is a EU-finded IST project with the goal of developing advanced tools and new production techniques for high-quality mixing of real and virtual content for film and TV productions. In particular, the project focuses on pre-production tools for set extension through image-based 3 0 modelling of environments and object. One key goal of the project is to achieve real-time in-studio previsu...

Phrase based statistic MT (PBSMT) is an important milestone in SMT. In the PBSMT, finding proper weights is an important issue. Currently, the MERT is widely adapted to optimize the weights of the models for various SMT approaches. For PBSMT, the N-best generation is an important factor affecting the performance of MERT according to our experimental results. In previous method on N-best generat...

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This paper provides a review of the security aspect of mobile banking applications. We employed blog mining as a research method to analyze blog discussion on security of mobile banking applications. Furthermore, we used the workflow technology to simulate real-life scenarios related to attacks on mobile banking applications. Insights are summarized to help banks and consumers mitigate the secu...

Many real life problems come from uncertain and dynamic environments, where the initial constraints and/or domains may undergo changes. Thus, a solution found for the problem may become invalid later. Hence, searching for robust solutions for Constraint Satisfaction Problems (CSPs) becomes an important goal. In some cases, no knowledge about the uncertain and dynamic environment exits or it is ...

The chapter sets the stage describing the background of real-time system in general and its computing intensive component in particular. The chapter describes basic definitions and concepts as related to the nature of real time systems, the development environment for typical real-time systems, selected issues related to the real-time programming and the accepted standards. The main objective o...

In Minimum Error Rate Training (MERT), the parameters of an SMT system are tuned on a certain evaluation metric to improve translation quality. In this paper, we present empirical results in which parameters tuned on one metric (e.g. BLEU) may not lead to optimal scores on the same metric. The score can be improved significantly by tuning on an entirely different metric (e.g. METEOR, by 0.82 BL...

This paper describes the development operated into MANY for the 2011 WMT system combination evaluation campaign. Hypotheses from French/English and En-glish/French MT systems were combined with a new version of MANY, an open source system combination software based on confusion networks decoding currently developed at LIUM. MANY has been updated in order to optimize decoder parameters with MERT...