Türk işaret dilinde söylem bütünlüğü ve hareket analizi: Deneysel ve hesaplamalı bir yaklaşım

Theories of linguistic efficiency, such as Zipf's (1949) law, claim that languages reduce effort by favoring simpler or more economical forms whenever possible. Although this claim has widely been tested and confirmed in spoken languages (e.g., Givon, 1983; Gundel, Hedberg, & Zacharski, 1993), it has not been addressed to the same extent in sign languages. This thesis investigates how such theories would be realized in Turkish Sign Language (TİD) through discourse cohesion and phonetic reduction in the narratives of TİD. With a story-retelling production experiment, discourse cohesion has been analyzed using a quantized measure of accessibility adapted from Ariel's (1990) framework. In particular, I examine referring expression forms (e.g., nominal versus verbal) that native and late-signing deaf adult TİD signers employ in narratives. The articulatory phonetic aspect of narratives has been analyzed using MediaPipe, an open-source computer vision tool. The results of the discourse cohesion experiment indicated a strong relationship between the cognitive accessibility scores of referents and the discourse context (e.g., first mention, maintenance, re-introduction), type of the referring expression, and age of acquisition in TİD, which aligned well with previous research on spoken language and other sign languages. The results of the computational phonetic analysis showed the forms that TİD signers used underwent phonetic reduction as the cognitive accessibility of a referent increased. They had shorter duration, smaller hand movement, and narrower signing space. Age of acquisition or delayed first acquisition did not significantly affect these measures except for duration, in which native signers retold the events faster than late signers. In conclusion, this thesis reconciles discourse cohesion and phonetic reduction within the framework of linguistic efficiency by offering a novel methodology to analyze signed discourse using both an experimental and computational approach.