This paper outlines a basic block level test translation tool for analog systems. Test translation aims at minimizing DFT overhead in a hierarchical test translation scheme to meet the ever increasing integration, performance and test re-use requirements. The concept of analog signal propagation and necessary signal attributes are introduced to achieve e ective and accurate test translation. A ...

Speaking as an initial goal in language teaching and learning has relationships with many variables including listening, reading, writing, knowledge of vocabulary as well as grammar. The present study mainly aims at examining the relationship between translations and speaking fluency. For this purpose and following an experimental design, three groups of Iranian advanced EFL learners were...

It is substantiated that particular features of pragmatics are teachable, and instruction is both necessary and effective. Determining what kind of intervention is most effectual for facilitating learners’ pragmatic development has been a central issue for researchers. To respond to the inconclusive findings in intervention studies and to extend the instructional studies in L2 pragmatics to les...

Arabic segmentation was already applied successfully for the task of statistical machine translation (SMT). Yet, there is no consistent comparison of the effect of different techniques and methods over the final translation quality. In this work, we use existing tools and further re-implement and develop new methods for segmentation. We compare the resulting SMT systems based on the different s...

Predicate-argument structure contains rich semantic information of which statistical machine translation hasn’t taken full advantage. In this paper, we propose two discriminative, feature-based models to exploit predicateargument structures for statistical machine translation: 1) a predicate translation model and 2) an argument reordering model. The predicate translation model explores lexical ...

In this paper we use the popular phrasebased SMT techniques for the task of machine transliteration, for English-Hindi language pair. Minimum error rate training has been used to learn the model weights. We have achieved an accuracy of 46.3% on the test set. Our results show these techniques can be successfully used for the task of machine transliteration.

Statistical Machine Translation (SMT) is a well-known and well established datadriven approach used for language translation. The focus of this work is to develop a statistical machine translation system for Sri Lankan languages, Sinhala and Tamil language pair. This paper presents a systematic investigation of how SinhalaTamil SMT performance varies with the amount of parallel training data us...