Spoken Features of the Robbery Defendants in Court

Author(s):
Article Type:
Research/Original Article (دارای رتبه معتبر)
Abstract:
Forensic Linguistics is a new and interdisciplinary branch of applied linguistics and law that analyzes oral and written legal texts by using language tools and linguistic evidences and helps in detecting crime. The goal of present research is to obtain spoken features of robbery defendants in order to provide a unique conversation of thieves in detection of crimes. The authors are trying to describe and explain speech of robbery defendants in Semnan province judicial system from the perspective of Forensic Linguistics.The results show that the robbery defendants by using many linguistic principles such as high modality, activism deletion, infelicitous utterance, illocutionary act try to gain interrogators confidence. Investigation of lawsuits details show that robbery defendants in their defenses use linguistic principles differently. In particular, they use in their speech modality for 29%, contradictions for 16%, activism deletion for 14%, presupposition for 10%, speech acts for 3%, implicature for 1% and middle voice construction for 0/5%. The methodology of the research is descriptive-analytic and its purpose is to describe and explain the spoken features of the robbery defendants according to linguistic principles from the perspective of forensic linguistics. According to the research topic that it describes and analyzes the spoken features of the robbery defendants, we have selected four robbery cases from Semnan prosecutors. The four cases have been read in full and in rows from the initial stages of investigation to interrogations and trials and the linguistics tools examined, have been identified, extracted and analyzed.
Also results suggest that attention to features and elegances of language like low modality, contradiction in speech, activism deletion, presupposition, implicature; middle voice construction and Gricean Cooperative Principles can help investigators and judges at crime detection.
Language:
Persian
Published:
Language Related Research, Volume:8 Issue: 7, 2018
Pages:
91 to 116
https://magiran.com/p1810630  
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