Persian

This study compares and contrasts lexical cohesion in English and Persian abstracts of Iranian medical students’ theses to appreciate textualization processes in the two languages. For this purpose, one hundred English and Persian abstracts were selected randomly and analyzed based on Seddigh and Yarmohamadi’s (1996) lexical cohesion framework, a version of Halliday and Hasan’s (1976) and Halliday’s (1985) taxonomies. For contrastive analysis, the SPSS package was used. The results revealed some similarities and differences in the use of lexical cohesion sub-categories in the parallel English and Persian texts. The occurrence of all sub-types is nearly the same in the two groups of texts and the two- tailed t-test employed showed that the differences are not statistically significant. Both languages exhibit a general tendency in using repetition, but synonymy and meronymy are the least used sub-categories. Regarding the density of the texts, the analysis indicates that Persian abstracts are denser than their corresponding English ones.

Articles in general and definite articles in particular can create problems even long after all other aspects of English have been mastered. The present article investigated the learnability problems related to the acquisition of count-mass distinction of English nominals by Persian L2 learners. The theoretical underpinning of the study is the interpretability hypothesis (Tsimpli & Dimitrakopoulou, 2007) arguing that the features which are semantically interpretable can be acquired. To this end, 50 learners constituted the participants of the study and completed a forced-choice elicitation task requiring the use of articles. The results of the study substantiated the interpretability hypothesis. Nonetheless, the advanced L2ers showed a conservative behavior in the mass context. They significantly opted for a/an in wide scope indefinite non-referential de/re context. The findings reveal that article suppliance creates more learnability problems in the plural and indefinite mass contexts compared to the count singular ones.

Avoiding the current terminology debates in the literature on politeness research and following a variational pragmatics approach, this study attempted to illuminate how appropriacy/ inappropriacy is realized in Persian language in light of five speech acts of introduction, apology, refusal, congratulation, and condolence. Additionally, it was aimed to see to what extent appropriacy/ inappropriacy is a function of variables such as age, gender, job, and level of education. In order to achieve this aim, 300 participants (m=150, f=150) completed an Open-ended Production Test (OPT) consisting of twenty situations. Analyzed within a two-component part variational pragmatics framework; namely pragmatic level and social factors, the data revealed that the variables in the study in quite different forms guide the expectations, perception and performance of the participants in the study. Giving an appropriacy (Marked/unmarked) taxonomy of the study speech acts in Persian, it is illustrated how, in most cases, the norms of appropriate verbal behavior seem to be subject to the variables of the study. It was further shown that talk and acts between speakers at a social situation are governed by converging and diverging norms in different communities of practice in Persian. Thereupon, the study can highlight the significance of including variational perspective on conventions of language use for language teaching.

This study is to determine how bilingualism could influence the list of Persian basic color terms and their order. Using a monolingual Persian and a bilingual Kurd sample students, and a color list task, it is assumed that bilingualism could change the ordering of the non-basic color terms in the second language, but not the basic ones. Another assumption is that, the old usual methods for obtaining mean position and saliency, based on Sutrop (2001) would not determine the BCTs in Persian. The data suggest that Persian has 6 BCTs; Qermez, Âbi, Sabz, Zard, Siyâh, and Sefid. The BCTs are retrieved by monolinguals much faster than bilinguals. Mean Position and frequency in school and university students had differences in number supporting the hypothesis that staying for more than two years in a bilingual environment and L2 use frequency are the two effective factors in BCTs order.

Section 115 of Iranian constitution reads: "The president should be among the political, religious 'rejal' …". The word 'rejal' taken from Arabic language means 'men'. Some Iranian politicians believe that the word has the same meaning in Persian, therefore, women cannot lead the country as presidents; while, others argue that 'rejal' can now refer to both sexes, therefore women can be elected as presidents. This, study tackles the issue from a sociolinguistic perspective. To do this, we need to find if the word 'rejal' is now a Persian word borrowed from Arabic, or, it is an Arabic word to which Persian speakers switch. About eleven hours of sociolinguistic interviews were conducted with 10 Persian speakers and all nouns (Arabic or Persian) were extracted from the data and later subjected to analyses to describe the linguistic behavior of each category in its own context. Then the behavior of nouns in each context is compared to that of the other contexts. Our findings show that Arabic origin nouns are found to be behaving like Persian nouns, they have, therefore, been borrowed into Persian and have Persian connotations and functions. Evidence is, therefore, presented to the 'Persianness' of 'rejal', shedding scientific light on a political problem.

This study aims at ascertaining a framework that would account for the Persian data. We scrutinize all data occurring in the selected corpus, and describe how they usually work on the basis of the two following variables: power and intimacy. According to our investigation, the use of terms of address in Persian is affected by age, sex, occupation, ideology, political and social position of the interlocutors. These variables can be stated as a result of the investigation of older material – such as qualitative analysis of observations followed by unobtrusive note taking of contemporary use, a corpus of several plays, travel accounts, interviews, TV, radio and careful observation terms used to address today. The above-mentioned variables indicate a strong relationship between social structures and address terms in Persian.

This paper aims at describing the mechanism of German loanwords adaptation with respect to constraints of Persian language and within OT framework. Consequently the adaptation of consonant clusters and diphthongs as well as the phonemes substituted in loanwords will be examined. Prince and Smolensky’s (1993) Optimality Theory with its key notions of faithfulness and markedness constraints is suited to model this aspect of linguistic competence. So in this research a number of 30 German loanwords were selected as research data of which some were collected through the library method from written resources and the rest are the trade names of German Products that are collected through a field work. Descriptive analysis of the mentioned data within Optimality Theory comes into valuable linguistic conclusions such as: “In Persian, initial consonant clusters of German loanwords are broken up through vowel epenthesis which is mostly identical to the vowel of the second syllable.”

This study investigates the morphological phenomenon known as plurals-in-compounds effect by analyzing responses given by 25 Persian-speaking children. The children, ranging in age from 3.5 to 13, were divided into six groups and asked questions like what do you call someone who verb-s [ regular/irregular ] plurals? that required them to form synthetic compounds such as car-stealer . Results indicated that when the nouns in the questions addressed to the children were regular plural, the non–heads in the compounds were predominately singular. Moreover, the children’s responses to questions containing irregular nouns showed that they preferred non–compound Agent ( singular N ) over compounds containing either singular or irregular plural nouns. The findings are in line with the specifications of Kiparsky's (1982) level-ordering model which bans plural morphology inside compounds. It was also revealed that the children’s compound construction relied on both structural and semantic constraints.

This study addresses the acquisition of the morphological markers in Persian learners of English as a foreign language. To this end, the accuracy order of nine morphemes including plural –s, progressive –ing, copula be, auxiliary be, irregular past tense, regular past tense –ed, third person –s, possessive -ʼs and indefinite articles was studied in 60 teenage Persian EFL learners. Placement and proficiency tests and a demographic questionnaire were employed to collect the data. The total production of 2160 morphemes was manually checked, classified, and counted to rank their acquisition order. The learners’ accuracy order was ranked in a decreased order from 1 to 9 as follows: regular past tense, auxiliary be, copula be, present progressive tense, indefinite articles, plural –s, possessive -ʼs, irregular past tense and third-person singular –s. The Spearman correlation showed that Persian students’ accuracy order had a moderate and weak relationship with the accuracy order of ESL and EFL learners, respectively. This finding proves that Persian EFL learners do not learn English grammatical morphemes in a natural order. Moreover, the universal grammar does not remain fully in these learners. The minor role of UG in EFL acquisition also indicates the important role of transfer in foreign language learning.

Although Persian and English share many common phonemes, there are some phonological features that are present in English but absent in Persian which tend to lead to mispronunciation on the part of Persian learners of English, mostly through negative transfer. The present research assesses the efficacy of a communicative framework in improving Iranian adult EFL learners’ pronunciation of five English phonemes absent in the phonological system of Persian. Thirty EFL learners, divided into experimental and control groups, participated in the training course which lasted 22 sessions (330 minutes). The experimental group was instructed using the communicative framework for teaching pronunciation while the control group received traditional methods of pronunciation teaching. The pronunciation quality of these sounds were then assessed by four native and four non-native English teachers as well as by the PRAAT speech analysis software in the case of the vowels. Although no significant difference was detected between the experimental and control groups with regard to posttest results, a positive trend was observed in favor of the experimental group regarding specific features (e.g., formant frequencies, duration, center of gravity) of the problematic sounds.

Languages as living and dynamic structured systems were influenced at the very first moments of the COVID-19 pandemic as they became medicalized by the use and practice of various jargons and technical terms. Meanwhile, homebound individuals around the world started to create a COVID-19 pandemic-related lexical-overload of neologisms (Coroneologisms or Corona coinages) in different languages which started to spread across the globe by mass media, and some of them even entered the official databases of the well-known dictionaries and Wikipedia corpora. This study was a scrutinized attempt to explore the English vs. Persian (Farsi) Coroneologisms across various Extensible Markup Language (XML) corpora and a huge body of E-resource discourses (websites, social media, and news channels and forums) based on embedded mixed-method design to provide a comprehensive insight into their types, structures, and meanings. To provide a better understanding of how and why particular Coroneologisms were created in terms of social, cultural, or political contributing factors, they were investigated based on the reflections of a series of sociolinguistic focus-group E-interviews with 184 volunteer English and Persian native speakers. This study might provide implications for sociolinguistics, corpus-based language studies, lexicographers, designers of corpora, etymologists, and discourse analysts in English and Persian.

We present FarsWikiKG, a Persian knowledge graph extracted from Wikipedia. Wikipedia infoboxes have been used as a valuable resource for building knowledge graphs in recent years. FarsWikiKG consists of more than 2 million entities, as well as 5.7 million facts about the entities. Using Wikidata, we constructed an ontology with more than 6000 classes representing entity types. As the second Persian knowledge graph, which has the ability of self-update, FarsWikiKG shows improvement on NLP tasks, especially question answering systems. Although FarsWikiKG is a dynamic knowledge graph, our evaluation shows a coverage of 90% on Persian Wikipedia pages. As Wikipedia information is constantly changing, a fixed knowledge graph can provide unstable data to the user. The proposed system, in addition to solving the problem of unstable data, reduces the need for experts to extract and construct knowledge graphs manually. Storing information in RDF as a standard method of storing knowledge graph information, FarsWikiKG allows NLP systems to run SPARQL queries on it.

The current study aims to investigate how Iranian EFL students make use of compliments in Persian and English. To that end, 50 students majoring in English as a foreign language from Isfahan and Tehran, and Sheikhbahaee universities were asked to respond to a Discourse Completion Test consisting of six situations in both English and Persian. They were asked to put themselves in those situations and respond to the compliments made on them. The results of the study showed that in addition to pre-existing categories of compliment responses, Iranians made use of other strategies not included in the pre-existing categories of compliments. Furthermore, in both English and Persian languages, students made use of compliments in the same order: accept, evade and reject strategies. The results of this study could add to crosscultural findings, differences or similarities regarding compliments as a beneficial way of studying speech acts.

La linguistique contrastive préserve toujours son importance en tant que lieu de rencontre de différentes structures syntaxiques et sémantiques dont la comparaison contribue à la clarification des points de ressemblances et de différences entre les langues étudiées. La causativité constitue une propriété universelle de la grammaire des langues. Autrement dit, chaque langue possède ses propres moyens pour encoder cette notion cognitive de base. L’objectif de ce travail a été de préciser les différentes constructions linguistiques à travers lesquelles on peut exprimer, en français et en persan, les sentiments causés sous l’impulsion d’un facteur extérieur. L’étude réalisée dans cet article a scruté diverses propriétés sémantiques (aspect, polarité, intensité) des constructions causatives dans les deux langues. Ce qui est au centre de cette recherche est donc de savoir comment les deux langues française et persane s’arrangent pour provoquer la joie et la surprise. L’hypothèse principale en est que le persan est doté d’un nombre considérable de causatives morphologiques. L’analyse des résultats prouve que la structure causative, en persan, était morphologique à l’inverse du français qui exprime cette notion à l’aide d’une structure syntaxique. Quant à l'aspect sémantique de l’expression causative de la joie et de la surprise, nous pouvons constater que la classe des « Vcaus neutres » représente le plus grand effectif, de l’ensemble des Vcaus en combinaison avec les Némot en français et en persan.

This paper discusses the use of Persian in comparison with Dari, a dialect of Persian language used in Kerman, one of the cities of Kerman Province located in southeast Iran. It is based on a random selection of 47 subjects from different sex, age, and occupational groups of Zoroastrian people with different levels of education in seven domains, i.e. family, friendship, neighborhood, transaction, education, government, and employment. In this study, the subjects were asked to determine which language they use in different domains on Likert’s 4-point scale. After collecting the data by the use of a questionnaire with 30 situations in the seven domains and analyzing them, the researcher concluded that there is a Persian-Dari diglossia in Zoroastrian speech community in which Dari functions as the Low language whereas Persian is the High one. As a matter of fact, Dari has been restricted to family domain and the young generation has lost it to a large extent.

Communicative and natural processing of language in the world of translation is substantiated through simultaneous decoding and encoding of information in the source and target languages. The researchers analy zed pragmatic strategies and approaches undertaken by the Persian and Kurdish translators of the Quranic discourse marker thumma. The source text corpus was selected randomly and the target text parallel corpora were selected based on purposive sampling. Theoretical perspectives in pragmatics and translation were employed in the analysis of parallel corpora in this investigation. The results revealed that various types and combinations of the Kurdish and Persian temporal discourse markers were utilized by these translators. Moreover, other Kurdish and Persian elaborative, contrastive, and inferential discourse markers were also used in rendering the discourse marker thumma in the Quran. This dynamic approach to the construction of discourse was substantiated based on the realization of different conventions in the construction of discourse in different languages and cultures. This dynamic system in the construction of a proper discourse for the readers is verified based on the application of different theories in discourse analysis and pragmatics and the application of context and text-sensitive strategies in the process of translation. The characteristics, bases, and resources of these dynamic translation strategies are discussed based on pragmatic awareness rising in various aspects of translation education and some suggestions were offered in the application of the findings in syllabus design, translation evaluation, and rethinking of approaches in lexicography.  

Paralinguistic features are indispensable and crucial aspects of communication without which any utterance would lose its identity. On the other hand, confusion in cross-cultural communication is most often assigned to paralinguistic features. Despite the significant importance of paralinguistic clues in humans’ communication, only limited studies have tackled this issue. More specifically, despite the fact that paralinguistic features are culturally different, no study has investigated the possible relationship between these features and speaking performance of Persian-speaking learners of English. Hence, with this existing gap in the literature, in this study, we tried to scrutinize the impact of paralinguistic cues upon EFL learners’ speaking fluency in the Persian setting. To this objective, we recruited 40 first-year undergraduate female students of Linguistics at the University of Gonabad, utilizing non-random sampling method. Their English proficiency level was determined as lower-intermediate via the administration of Quick Oxford Placement Test. In our pre-test post-test experimental research, we allocated a five-week span of instruction for the purpose of teaching paralinguistic clues to the experimental group to see whether it could have a significant positive impact upon their speaking performance. The instrument we utilized to evaluate speaking capability of our participants was Researcher-Made Speaking Test. The results of our study demonstrated that utilizing paralinguistic features boosted students’ speaking capability. On the light of our finding, it could be concluded that paralinguistic features could be employed for the first-year undergraduate students to enhance their communicative performance. Future studies in diverse EFL settings, could shed light on this conclusion.

Within the Minimalist Program (MP), Relative clauses (RCs) are considered complementizer clauses (CPs) containing a C with an edge feature [EF] in the form of [wh] and [EPP] but no tense feature. This study investigates Persian RC derivation based on MP. By proposing two approaches, namely: (1) ‘ ke -movement’ and (2) ‘null wh-operator (OP) movement’, we will consistently argue and show that the null wh-OP approach provides an appropriate generalization for Persian restrictive RCs. Adopting the latter, the results display Persian RCs can be analyzed as CPs with a null wh-OP assuming to undertake wh-movement as copying and deletion from different syntactic positions, i.e., subject, direct object, object of preposition, etc. This operator allows a small pro in the subject position, leaving an optional null copy, either allowing an optional resumptive pronoun (RP) behind in direct object position or attaching to the verb; and obligatorily in indirect object and object of preposition positions as well as Ezafe-construction. Also, the edge feature of the probe, the complementizer ke , attracts the null wh-OP to Spec-C, for checking and valuing the unvalued [wh] and [EPP] features. The long relative clause derivations can, correspondingly, work as expected by the successive cyclic movement of OP through intermediate Spec-C positions as well.

Sentiment analysis is the process of identifying and categorizing people’s emotions or opinions regarding various topics. The analysis of Twitter sentiment has become an increasingly popular topic in recent years. In this paper, we present several machine learning and a deep learning model to analysis sentiment of Persian political tweets. Our analysis was conducted using Bag of Words and ParsBERT for word representation. We applied Gaussian Naive Bayes, Gradient Boosting, Logistic Regression, Decision Trees, Random Forests, as well as a combination of CNN and LSTM to classify the polarities of tweets. The results of this study indicate that deep learning with ParsBERT embedding performs better than machine learning. The CNN-LSTM model had the highest classification accuracy with 89 percent on the first dataset and 71 percent on the second dataset. Due to the complexity of Persian, it was a difficult task to achieve this level of efficiency. The main objective of our research was to reduce the training time while maintaining the model's performance. As a result, several adjustments were made to the model architecture and parameters. In addition to achieving the objective, the performance was slightly improved as well.