Difficulties faced by second language learners of Arabic when translating Tamil sentences into Arabic

Adaptive Feedback Message Generation for Second Language Learners of Arabic

This paper addresses issues related to generating feedback messages to errors related to Arabic verbs made by second language learners (SLLs). The proposed approach allows for individualization. When a SLL of Arabic writes a wrong verb, it performs analysis of the input and distinguishes between different lexical error types. The proposed system issues the intelligent feedback that conforms to ...

second language acquisition of telicity and aspect by persian learners of english

این تحقیق از دو قسمت اصلی تشکیل شده است: در قسمت اول فراگیری ختمیت به ویژه درک و تولید اینگونه جملات توسط فراگیران ایرانی زبان انگلیسی مورد بررسی قرار گرفته است. قضاوت تعدادی انگلیسی زبان بر روی این جملات نیز هدفی دیگر بود که در این رساله بررسی شده است. از موضوعات دیگر تفاوت بین نشانه های ختمیت در زبان انگلیسی و فارسی و تاثیر زبان اول فراگیران در درک و تولید اینگونه جملات است. در قسمت دوم استفا...

Third-year Students’ Difficulties in Translating Computing Terms from English into Arabic

Towards Translating Natural Language Sentences into ASP

We build upon recent work by Baral, Dzifcak and Son that define the translation into ASP of (some classes of) natural language sentences from the lambda-calculus intermediate format generated by CCG grammars. We introduce automatic generation of lambda-calculus expressions from template ones, thus improving the effectiveness and generality of the translation process.

Parse Trees of Arabic Sentences Using the Natural Language Toolkit

We develop a framework for using the Natural Language Toolkit (NLTK) to parse Quranic Arabic sentences. This framework supports the construction of a treebank for the Holy Quran. The proposed model succeeds in parsing different Quranic chapters (Suras) in addition to Modern Standard Arabic (MSA) sentences. The availability of such parser will be useful in various natural language processing app...