Department of Linguistics

In  this  paper,  first  some  English  and  Persian  onomatopoeia  and  sound  symbolism  have
randomly  been  selected  from  different  internet  sites  and  books  to  be  contrastively  compared
in  order  to  see  the  differences  and  similarities  in  their  kinds  of  phonemes,  and  then  their
application  in  the  discourse  of  advertisements  is  studied.  Regarding  the  first  hypothesis,  we
came  to  the  conclusion  that  some  onomatopoeic  activities  in  Persian  and  English  were
different  especially  concerning  animal  voices  which  can  be  due  to  the  different  species  of
animals,  different  phonological  or  morphological  systems  of  every  language,  but  the  rest
onomatopoeic  sounds  were  to  some  extent  similar  having  minor  differences  phonologically
like  in  their  syllables.  According  to  the  second  hypothesis,  we  can  not  only  make  use  of
onomatopoeia  in  our  advertisements  like  "Mmmm  Cookies"  and  "Pepsi  puffs  but  also  of  the
potential  ability  of  sound  symbolism;  for  instance,  manufacturers  can  use  fricative  sounds  to
label  their  detergents  more  successfully  due  to  the  likely  innate  potential  of  fricative  sounds
as scratching, coarseness and wounding.

DUE  TO  THE  FACT  THAT  WWW.TRANSLATE.GOOGLE.COM  IS  AN  ACTIVE  TRANSLATION
SITE,  AND  THERE  MAY  BE  PROBABLE  ERRORS  IN  THE  TARGET  TEXT,  AND  DUE  TO  THE
LACK OF AN APPROPRIATE FRAMEWORK FOR ASSESSING THE PROCESS OF PERSIAN INTO
ENGLISH  TEXTS,  IT  SEEMS  HALLIDAY'S  SYSTEMATIC  FUNCTIONAL  GRAMMAR  (SFG)
PROVIDES  A  SUITABLE  FRAMEWORK  TO  ASSESS  AND  PREDICT  KINDS  OF  ERRORS  TO  BE
EDITED. BECAUSE THE TWO LANGUAGES HAVE DIFFERENT CONSTITUENCY ORDERS AND
MORPHOLOGICAL  TYPOLOGY,  SIGNIFICANT  LEXICO-GEAMMAR  ERRORS  CAN  BE
EXPECTED;  OUT OF 350 CLAUSES REGARDING PHD THESIS WHICH WERE TRANSLATED BY
GOOGLE  TRANSLATE,  26  BELONGED  TO  THE  VERBAL  PROCESS  OF  THE  EXPERIENTIAL
METAFUNCTIONS OUT OF WHICH 16 CLAUSES BELONGED TO TRANSITIVE (9 UNMARKED
AND  7  MARKED)  AND  10  TO  INTRANSITIVE  PERSIAN  CLAUSES;  HERE  3  UNMARKED
TRANSITIVE  PERSIAN  CLAUSES  (SOV),  3  MARKED  TRANSITIVE  PERSIAN  CLAUSES  (SVO),
ONE  PRO-DROP-MARKED  TRANSITIVE  PERSIAN  CLAUSE  (SOV),  AND  4  INTRANSITIVE
PERSIAN  CLAUSES  HAVE  BEEN  CHOSEN  TO  BE  STUDIED  AND  EDITED.  THESE  CLAUSES
WERE  CLASSIFIED  AND  EDITED  IN  CONSTITUTION  CLASSIFICATION  AND  EDITION  BOX,
THEN  THEIR  ERRORS  WERE  EVALUATED  BY  HAR  TRANSLATION  EVALUATION  BOX
DESIGNED  BY  THE  AUTHORS  IN  WHICH  ALL  THE  TERMS  WERE  DERIVED  FROM  SFG.
GOOGLE TRANSLATE HAD FEWER AND LIGHTER ERRORS WHEN IT TRANSLATED PERSIAN
MARKED  TRANSITIVE CLAUSES OF VERBAL PROCESS WITH THE CONSTITUENCY ORDER OF
SVO, THE SAME AS ENGLISH UNMARKED CONSTITUENCY ORDER SVO, AS WELL AS WHEN
IT TRANSLATED  INTRANSITIVE  PERSIAN CLAUSES OF VERBAL PROCESS OV, THE SAME AS
Modern Journal of Language Teaching Methods (MJLTM)
Vol. 6, Issue 5, August 2016 Page 494
ENGLISH  INTRANSITIVE  CLAUSE  CONSTITUENCY ORDER  OF  OV; BUT IT HAD  MORE  AND
HEAVIER  ERRORS  WHEN  IT  TRANSLATED  PERSIAN  UNMARKED  TRANSITIVE  CLAUSES
WITH THE CONSTITUENCY ORDER OF SOV, OPPOSITE TO ENGLISH SVO

Zargari is a secret language commonly used among Persian-speaking
families in Tehran. The present paper aims to describe and analyze Zargari
secret language within the framework of the generative approach. Evidently
Zargari is a natural language with frequent manipulation of repetition and
vowel harmony in the syllables. The manipulation in Zargari consists in the
insertion of a ZV-syllable within the syllabic pattern of the words.

Valency lexicons are valuable resources for natural language processing. The need for new resources for languages encourages researchers to collect new datasets. One of the most important datasets is valency lexicons. In valency lexicons, information about obligatory and optional complements of words is annotated at the syntactic and semantic levels. In this paper, we report the development of the first syntactic valency lexicon of Persian verbs. This lexicon is part of the Persian Dependency Treebank Project. The lexicon consists of 4282 distinct verb lemmas and 5429 distinct verb-valency pairs.

Subject salience in SOV and SVO word orders as a result of agent animacy 1 Abstract The present paper presents a cognitive account of how animacy leads to the initial positioning of the subject (subject salience) in SOV and SVO word orders. Subject salience has been paid attention to in the literature from a semantic and functional viewpoint. In this paper, we argue that clauses with SOV and SVO word orders are diagrammatic icons in that they reflect how the prototypical transitive action scenario is conceptualized by the human mind. In such a scenario, the agent receives the most attention from the human viewer and is conceptualized more saliently than the other elements of the scenario. As a result, the linguistic counterpart of the agent, i.e. the subject is mentioned before the object and the verb to show its salient position. The reason for the more attention paid to the agent, we believe, is that in a prototypical transitive action scenario, the agent is animate and as research shows, animacy is evolutionarily of great importance to the human species.