List of Articles Farsi language

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  1 - Teaching Farsi Compound Verbs to non-Persian Speakers
  زينب  محمد ابراهيمي حسن  شاهی‌پور
  The category of compound verbs is one of the most interesting, subtle and yet complex part of syntactic researches that has attracted the attentions of many linguists and teachers teaching a second/ foreign language. Analyzing the structure of compound verbs in spoken s More

  The category of compound verbs is one of the most interesting, subtle and yet complex part of syntactic researches that has attracted the attentions of many linguists and teachers teaching a second/ foreign language. Analyzing the structure of compound verbs in spoken standard Farsi language in terms of Government and binding theory, and using a new scientific method of teaching language and vocabulary, the present research tries to provide a new practical and effective way of teaching Farsi compound verbs to the speakers of languages other than Farsi. According to the finding of the research, the compound verbs can be divided into two groups: one-argument verbs and multi-argument verbs. At elementary levels, it is better to start teaching with the first group. The second group should be taught at higher levels. Moreover, it seems appropriate to use spoken materials that have already been recorded in real communication contexts. Manuscript profile
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  2 - A Semantic Approach to Person Profile Extraction from Farsi Web Documents
  Hojjat Emami Hossein Shirazi ahmad abdolahzade
  10.7508/jist.2016.04.004
  Entity profiling (EP) as an important task of Web mining and information extraction (IE) is the process of extracting entities in question and their related information from given text resources. From computational viewpoint, the Farsi language is one of the less-studie More

  Entity profiling (EP) as an important task of Web mining and information extraction (IE) is the process of extracting entities in question and their related information from given text resources. From computational viewpoint, the Farsi language is one of the less-studied and less-resourced languages, and suffers from the lack of high quality language processing tools. This problem emphasizes the necessity of developing Farsi text processing systems. As an element of EP research, we present a semantic approach to extract profile of person entities from Farsi Web documents. Our approach includes three major components: (i) pre-processing, (ii) semantic analysis and (iii) attribute extraction. First, our system takes as input the raw text, and annotates the text using existing pre-processing tools. In semantic analysis stage, we analyze the pre-processed text syntactically and semantically and enrich the local processed information with semantic information obtained from a distant knowledge base. We then use a semantic rule-based approach to extract the related information of the persons in question. We show the effectiveness of our approach by testing it on a small Farsi corpus. The experimental results are encouraging and show that the proposed method outperforms baseline methods. Manuscript profile
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  3 - Letter to Sound Conversion for Persian Language Using Multi Layer Perceptrons
  M. Namnabat M. M. Homayounpour
  Construction of letter to sound (LTS) conversion systems in Persian is a difficult task. Because of the omission of some vowels in Farsi orthography, these systems in general have low efficiencies. In this paper, the structure of a letter to sound system, having three-l More

  Construction of letter to sound (LTS) conversion systems in Persian is a difficult task. Because of the omission of some vowels in Farsi orthography, these systems in general have low efficiencies. In this paper, the structure of a letter to sound system, having three-layer architecture, was presented. The first layer is rule-based, and the second layer consists of five multi layer perceptron (MLP) neural networks and a controller section for pronunciations determination. The third layer has a MLP network for detection of geminated letters by using results obtained from the previous steps. The proposed system is designed to produce rational pronunciations for every word, where the rational pronunciation means a phonetic transcription, which follows the correct Farsi syllabification structure and the obvious rules of phonetics. The authors have achieved 88% and 61% correct letters and words performance respectively, which is quite satisfactory for a Farsi language LTS system. The correct letter criterion is the percentage of letters for which the pronunciations have been determined correctly and the correct word criterion is the percentage of words for which the pronunciations of the constituting letters have been determined correctly. Manuscript profile