this study had two main steps. the first one was introducing and examining the long’s model of needs analysis (na) for distinguishing the general language needs. by doing the first step, we tried to recognize the shortages of long’s model, in the second step to realize the general language needs of persian language learners and find out what language functions are needed to be learned for gener...

Bilingual parallel corpora are very important in various filed of natural language processing (NLP). The quality of a Statistical Machine Translation (SMT) system strongly dependent upon the amount of training data. For low resource language pairs such as Persian-English, there are not enough parallel sentences to build an accurate SMT system. This paper describes a new approach to use the Wiki...

A novel technique is introduced for verb and inflection detection in Persian texts. This recognition can be useful for preprocessing phase in natural language processing (NLP) and text mining like partof-speech (POS) tagging and sentence boundary detection (SBD) in Persian texts. Our technique employs structural information of Persian verb for the first phase of this detection and then uses the...

This paper describes the latest developments in the PeEn-SMT system, specifically covering experiments with Grafix, an APE component developed for PeEn-SMT. The success of well-designed SMT systems has made this approach one of the most popular MT approaches. However, MT output is often seriously grammatically incorrect. This is more prevalent in SMT since this approach is not language-specific...

Persian is a challenging language in the field of NLP. Rightto-left orthography, complex morphology, complicated grammatical rules, and different forms of letters make it an interesting language for NLP research. In this paper we measure the effectiveness of a simple and efficient stemming algorithm, Perstem, on Persian information retrieval. Our experiments on the Hamshahri corpus at CLEF2009 ...

This article studies different aspects of a new approach to word sense disambiguation using statistical information gained from a monolingual corpus of the target language. Here, the source language is English and the target is Persian, and the disambiguation method can be directly applied in the system of English-to-Persian machine translation for solving lexical ambiguity problems in this sys...

Sense tagged corpora play a crucial role in Natural Language Processing, particularly in Word Sense Disambiguation and Natural Language Understanding. Since semantic annotations are usually performed by humans, such corpora are limited to a handful of tagged texts and are not available for many languages with scarce resources including Persian. The shortage of efficient, reliable linguistic res...

persian language has influenced arabic language in many different ways; especially in the lexical area of language. since many persian words have entered arabic language, this language has been affected by persian language and culture. many of these persian words can be found in an arabic lexicon called lesan-al-arab. the writers of this article have analyzed the arabic form of the word sepanjg...

This paper describes the participation of the University of Neuchâtel to the CLEF 2008 evaluation campaign. In the Persian ad hoc task, we suggest using a light suffixstripping algorithm for the Farsi language and the evaluations demonstrated that such an approach performs better than a simple light stemmer, an approach ignoring the stemming stage or a language independent approach (n-gram). Th...