The CMU Statistical Transfer Framework (Stat-XFER) is a general framework for developing search-based syntax-driven machine translation (MT) systems. The framework consists of an underlying syntaxbased transfer formalism along with a collection of software components designed to facilitate the development of a broad range of MT research systems. The main components are a general language-indepe...

One of the interesting issues regarding BIPA learning process is how similarities and differences source target languages (Indonesian language) are related to students’ understanding Indonesian language. This study what known as a cross-linguistic transfer. paper reviews theoretically transfer in Language for Foreign Speakers). employed descriptive-qualitative method. A qualitative method was u...

We present a simple method to improve neural translation of a low-resource language pair using parallel data from a related, also low-resource, language pair. The method is based on the transfer method of Zoph et al., but whereas their method ignores any source vocabulary overlap, ours exploits it. First, we split words using Byte Pair Encoding (BPE) to increase vocabulary overlap. Then, we tra...

This paper presents two instance-level transfer learning based algorithms for cross lingual opinion analysis by transferring useful translated opinion examples from other languages as the supplementary training data for improving the opinion classifier in target language. Starting from the union of small training data in target language and large translated examples in other languages, the Tran...

This study examined the role of the native language (L1) transfer in a non-native language (L2) acquisition of the there-insertion construction at the syntax-semantics interface. Specifically, the study investigated if Mandarin EFL learners would make overgeneralization errors in the situation where an L1 argument structure constitutes a superset of its L2 counterpart. Verbs of existence and ap...

One of the problems in spoken language translation is the enormous variety of expressions not found in text translation. This volume can lead to a sparse translation coverage. In order to tackle this problem, we propose a machine translation model where an input is translated through both source-language and target-language paraphrasing processes. In this paper, we discuss the source paraphrasi...

This paper aims at investigating the acquisition of Italian complex predicates by native speakers of Persian. Complex predication is not as pervasive a phenomenon in Italian as it is in Persian. Yet Italian native speakers use complex predicates productively; spontaneous data show that Persian learners of Italian seem to be perfectly aware of Italian complex predicates and use this familiar fea...