literary texts

In this study, corpus-based techniques were utilized in order to investigate the quantitative and qualitative features of adjectives across literary and technical texts. The corpus was composed of five literary novels and five engineering academic books in English. Seventy paragraphs were randomly drawn from each corpus and the frequency distribution of adjectives with respect to their position (attributive, predicative) and syntactic functions (descriptive, verbal, numeral, etc.) were tallied and summed. The results revealed that there is a significant difference in the frequency use of adjectives across the two corpora. From a register perspective, the high frequently use of adjectives in technical texts in comparison to literary texts (67.3% and 32.7%, respectively) may be due to the fact that almost all technical texts employ “expository” linguistic features which have a generally “informational purpose”, while most novels employ “narrative’’ linguistic features which have a direct functional association with the communicative purpose of telling a story of events which have occurred in the past. From a genre perspective, academic texts in engineering tend to be highly informational, non-narrative, and characterized by an impersonal style, whereas novels generally share the same primary communicative purpose of narrating a story whose purpose is to entertain.

Google Translate , a free multilingual machine translation service, developed by Google has attracted the attention of countless users due to its ease of use through modern means of mass communication, and has become the only translation tool in some areas. However, compared to human translation, these machine tools have not yet been able to deliver high-quality translations due to the complexity of translation process. Therefore, studying the modifications of machine translated texts is of great importance. Therefore, the current study aimed to explore the types of linguistic modifications of the texts translated from Persian into English through Google Translate. To this end, the abstracts of ten unpublished Persian literary articles intended to be submitted to Iranian journals were selected for the analysis. The selected abstracts were initially translated into English (target language) through Google Tra n slate from Persian (source language). To identify the kinds of changes needed to make them academically acceptable, the machine translated texts were all post edited. Then, the original Google translated texts and their post edited versions were compared to figure out the types of the applied modifications. The results of this qualitative study indicated that the linguistic post edition modification of the texts included tense, literal translation, redundancy, collocations, deletion of the main verb, word-choice and proper nouns.

The effect of reading and teaching literary texts on the development of productive skills of language learners has long been an eye-catching factor for researchers. Having determined the interest through analysis, the present study seeks to search the effect of literary texts on the enhancement of vocabulary usage and composition length of the EFL learners. To achieve the above-mentioned desire, a case study was designed, including the population of 15 intermediate EFL. The case was chosen from the language learners of the Velayat University of Iranshahr. They were supposed to read and discuss a literary text, the effect of which on their writing was later compared to a previously prepared composition, before the exposure of the literary text. A focus on the vocabulary range and composition length along with the progression of their ideas in writing revealed that literary text and the discussion session were highly influential on the above-mentioned features. They used more lexical resources from the literary text in their composition along with a longer and more comprehensive text in terms of progression.