Word prediction is the problem of guessing the words which are likely to follow in a given text segment by displaying a list of the most probable words that could appear in that position. In this research, we designed and implemented three word predictors for Persian. Our baseline is a statisticalbased system which uses language models. The first system uses word statistics; in the second one w...

The Statistical Machine Translation (SMT) systems are developed using sentence aligned parallel corpus. The difficulty is that there is no parallel corpus at the required measure for many language pairs. The preparation of large scale parallel corpus takes time and demands the linguistics skill. In the present work, the various issues of a quality parallel corpus and a technique that extracts p...

The OGI Multi-language Telephone Speech Corpus is designed to support research on automatic language identi cation and multi-language speech recognition. The corpus consists of up to nine separate responses from each caller, ranging from single words to short topic-speci c descriptions to 60 seconds of unconstrained spontaneous speech. The utterances were spoken over commercial telephone lines ...

Translation is not merely a mater of linguistics. The major goal the present paper to investigate relationship between ‘culture’ and ‘translation’. To this end, researcher drew on corpus from English Persian languages. findings indicated that although different languages, like Persian, employ linguistic forms, variety cannot be considered as real challenge. Since during process translation, sou...

This research sought to identify the translation strategies adopted by the translator in Persian translation of 'whatever after, Fairest of all' written by 'Sarah Mlynowski' based on Klingberg's model (1986). To achieve the objectives of the study, a qualitative content analysis design was selected for it. The corpus of the study consisted of 60 pages of the novel 'whatever after, Fairest of al...

This paper addresses some of the issues learned during the course of building a written language resource (called ‘Peykare’) for contemporary Persian. After defining five linguistic varieties and 24 different registers based on these linguistic varieties, we collected the texts for Peykare to do a linguistic analysis, including cross-register differences. For tokenization of Persian, we have pr...

The goal in the named entity recognition task is to classify proper nouns of a text into classes such as person, location, and organization. This is an important preprocessing step in many natural language processing tasks such as question-answering and summarization. Although many research studies have been conducted in this area in English and the state-of-the-art NER systems have reached per...

Although the parallel corpus has an irreplaceable role in machine translation, its scale and coverage is still beyond the actual needs. Non-parallel corpus resources on the web have an inestimable potential value in machine translation and other natural language processing tasks. This article proposes a semi-supervised transductive learning method for expanding the training corpus in statistica...