ISSN 0439-755X
CN 11-1911/B

Acta Psychologica Sinica ›› 2015, Vol. 47 ›› Issue (7): 878-889.doi: 10.3724/SP.J.1041.2015.00878

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Chinese Sign Language Lexical Recognition: Two Network Systems and Interaction Effect Among Sign Language Words

CHEN Suiqing1; ZHANG Jijia2; LI Yanxia3; ZHANG Huixia3   

  1. (1 School of Education, Guangzhou University, Guangzhou 510006, China) (2 Department of Psychology, Renmin University of China, Beijing 100872, China) (3 College of Municipal Works and Construction, Guangzhou University, Guangzhou 510800, China)
  • Received:2014-07-31 Published:2015-07-25 Online:2015-07-25
  • Contact: ZHANG Jijia, E-mail: Zhangjj1955@163.com

Abstract:

Sign language, as the first and natural acquisition language for deaf, is a language form that transfer information and interact thought by gesture, face expression and posture etc. Similar to oral language and written language, sign language also has a special grammar system representing sophisticated thought, subtle emotion and other abstract information. To date, most theories of word recognition have been proposed largely based on studies of spoken language, even though few studies have examined sign language lexical recognition. The comparison of signed and written language processing is necessary for reflecting general properties of the language recognition system. Based on the “Lexical and Semantic Network System” theory, effects of four variables including familiarity, complexity, iconicity, concreteness were investigated in Chinese Sign Language lexical recognition. Familiarity and complexity belonged to variables of lexical network system, iconicity and concreteness belonged to variables of semantic network system. Therefore, this paper not only focused on specific factors in sign language word recognition, but also the interaction between these factors in the two network system. The effects of familiarity, complexity, iconicity and concreteness of the Chinese Sign Language were studied by sign lexical decision mission with 3 experiments. In experiment 1, the variable of lexical familiarity was crossed with complexity; in experiment 2, the variable of lexical familiarity was crossed with iconicity; in experiment 3, the variable of lexical familiarity was crossed with concreteness. Participants were instructed to press the button for indicating whether the probe appearing on the screen was a legitimate sign or not. The non-signs were not the real Chinese Sign Language, but resembled real signs. All signs and non-signs were recorded by a digital camcorder. Signs were edited into video movie files and each individual sign clip was normalized in duration to 2500ms. The ANOVA on the reaction time showed a main effect of sign familiarity in three experiments: signs with higher familiarity were responded faster than the ones with lower familiarity. The complexity effect was significant, suggesting that signs from a low complexity were responded faster than signs from a high complexity. The main effects of both iconicity and concreteness showed that high iconicity and concreteness were responded faster than low ones. In addition, the interaction effect between lexical familiarity and iconicity was significant. High familiarity signs with a high iconicity were responded faster than those with a low iconicity. Moreover, no differences of concreteness were observed for high familiarity signs, but a facilitate effect of concreteness was significant for low familiarity signs. The results indicated that recognition of Chinese Sign Language related to two network systems: lexical network and semantic network. In summary, in this sign lexical decision mission experiment, the conclusions were as follows: (1) Besides the effects of familiarity, complexity, iconicity and concreteness in sign language lexical cognition, the interaction effect among them was also found; (2) Sign language lexical access related to lexical and semantic network system. In general, we proposed two-direction-mapping model in discussing sign language processing, in which both form- to-meaning and meaning-to-form directions were included.

Key words:  Chinese Sign Language, lexical recognition, lexical network, semantic network.