Hostname: page-component-cd9895bd7-lnqnp Total loading time: 0 Render date: 2024-12-27T22:32:20.695Z Has data issue: false hasContentIssue false
  • English
  • Français

Simulating cross-language priming with a dynamic computational model of the lexicon*

Published online by Cambridge University Press:  07 December 2012

XIAOWEI ZHAO  and
PING LI
XIAOWEI ZHAO*
Affiliation:
Emmanuel College
PING LI
Affiliation:
Pennsylvania State University
*
Address for correspondence: Xiaowei Zhao, Department of Psychology, Emmanuel College, 400 The Fenway Boston, MA 02115, USAzhaox@emmanuel.edu
Get access Rights & Permissions [Opens in a new window]

Abstract

Cross-language priming is a widely used experimental paradigm in psycholinguistics to study how bilinguals’ two languages are represented and organized. Researchers have observed a number of interesting patterns from the priming effects of both translation equivalents and semantically related word pairs across languages. In this study, we implement a self-organizing neural network model, DevLex–II, to simulate these two types of priming effects across Chinese and English. Specifically, our model incorporates a computational mechanism for simulating spreading activation based on the distance between bilingual words in the semantic space. The model also considers additional factors that modulate priming effects, such as the initial activation level of the prime words and the degree to which the target word can be recognized. Our model reveals differences with respect to the priming effects as a function of bilingual type (early versus late L2 learners), directions of priming (L1 to L2 versus L2 to L1), and types of priming (translation versus semantic priming). These simulated differences are compared with empirical findings from previous studies and discussed in the light of interactive and developmental theories of bilingual lexical representation.

Keywords

neural networkscross-language primingDevLex–IIspreading activationAoA
Type
Research Article
Information
Bilingualism: Language and Cognition , Volume 16 , Issue 2: Computational Modeling of Bilingualism , April 2013 , pp. 288 - 303
Copyright
Copyright © Cambridge University Press 2012

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Footnotes

*

Preparation of this article was supported by grants from the National Science Foundation (#0968369; #1057855) to PL and by a grant from the Faculty Development Committee at Emmanuel College to XZ. We would like to thank three anonymous reviewers for their valuable comments and suggestions on earlier versions of this article.

References

Altarriba, J., & Basnight-Brown, D. M. (2007). Methodological considerations in performing semantic- and translation-priming experiments across languages. Behavior Research Methods, 39 (1), 1–18.Google Scholar
Basnight-Brown, D., & Altarriba, J. (2007). Differences in semantic and translation priming across languages: The role of language direction and language dominance. Memory & Cognition, 35 (5), 953–965.Google Scholar
Collins, A. M., & Loftus, E. F. (1975). A spreading-activation theory of semantic processing. Psychological Review, 82, 407–128.Google Scholar
Dale, P. S., & Fenson, L. (1996). Lexical development norms for young children. Behavior Research Methods, Instruments, & Computers, 28, 125–127.Google Scholar
De Groot, A. M. B. (1992). Bilingual lexical representation: A closer look at conceptual representations. In Frost, R. & Katz, L. (eds.), Orthography, phonology, morphology, and meaning, pp. 389–412. Amsterdam: Elsevier.Google Scholar
Dijkstra, T., & Van Heuven, W. (1998). The BIA model and bilingual word recognition. In Grainger, J. & Jacobs, A. M. (eds.), Localist connectionist approaches to human cognition, pp. 189–225. Mahwah, NJ: Lawrence Erlbaum.Google Scholar
Dijkstra, T., & Van Heuven, W. J. B. (2002). The architecture of the bilingual word recognition system: From identification to decision. Bilingualism: Language and Cognition, 5 (3), 175–197.Google Scholar
Dimitropoulou, M., Duñabeitia, J. A., & Carreiras, M. (2011). Two words, one meaning: Evidence of automatic co-activation of translation equivalents. Frontiers in Psychology, 2, 188.Google Scholar
Finkbeiner, M., Forster, K., Nicol, J., & Nakamura, K. (2004). The role of polysemy in masked semantic and translation priming. Journal of Memory and Language, 51 (1), 1–22.Google Scholar
Forster, K. I., & Davis, C. (1984). Repetition priming and frequency attenuation in lexical access. Journal of Experimental Psychology: Learning, Memory, and Cognition, 10, 680–698.Google Scholar
Grosjean, F. (1998). Studying bilinguals: Methodological and conceptual issues. Bilingualism: Language and Cognition, 1, 131–149.Google Scholar
Harm, M. (2002). Building large scale distributed semantic feature sets with WordNet. Technical Report PDP-CNS-02–1, Carnegie Mellon University.Google Scholar
Hernandez, A., & Li, P. (2007). Age of acquisition: Its neural and computational mechanisms. Psychological Bulletin, 133, 638–650.Google Scholar
Hernandez, A., Li, P., & MacWhinney, B. (2005). The emergence of competing modules in bilingualism. Trends in Cognitive Sciences, 9, 220–225.Google Scholar
Jacquet, M., & French, R. (2002). The BIA++: Extending the BIA+ to a dynamical distributed connectionist framework. Comment. Bilingualism: Language and Cognition, 5 (3), 202–205.Google Scholar
James, D., & Miikkulainen, R. (1995). SARDNET: A self-organizing feature map for sequences. In Tesauro, G., Touretzky, D. S. & Leen, T. K. (eds.), Advances in neural information processing systems 7, pp. 577–584. Cambridge, MA: MIT Press.Google Scholar
Jiang, N. (1999). Testing processing explanations for the asymmetry in masked cross-language priming. Bilingualism: Lang and Cognition, 2, 59–75Google Scholar
Jiang, N., & Forster, K. (2001). Cross-language priming asymmetries in lexical decision and episodic recognition. Journal of Memory and Language, 44, 32–51.Google Scholar
Kiran, S., & Lebel, K. R. (2007). Crosslinguistic semantic and translation priming in normal bilingual individuals and bilingual aphasia. Clinical Linguistics & Phonetics, 21, 277–303.Google Scholar
Kohonen, T. (2001). The self-organizing maps (3rd edn.). Berlin: Springer.Google Scholar
Kroll, J., & Stewart, E. (1994). Category interference in translation and picture naming: Evidence for asymmetric connection between bilingual memory representations. Journal of Memory and Language, 33 (2), 149–174.Google Scholar
Li, P. (2002). Bilingualism is in dire need of formal models. Bilingualism: Language and Cognition, 5, 213.Google Scholar
Li, P., & Farkas, I. (2002). A self-organizing connectionist model of bilingual processing. In Heredia, R. & Altarriba, J. (eds.), Bilingual sentence processing, pp. 59–85. Amsterdam: Elsevier Science.Google Scholar
Li, P., Farkas, I., & MacWhinney, B. (2004). Early lexical development in a self-organizing neural network. Neural Networks, 17, 1345–1362.Google Scholar
Li, P., & MacWhinney, B. (2002). PatPho: A phonological pattern generator for neural networks. Behavior Research Methods, Instruments & Computers, 34 (3), 408–415.Google Scholar
Li, P., Zhao, X., & MacWhinney, B. (2007). Dynamic Self-Organization and children's word learning. Cognitive Science, 31, 581–612.Google Scholar
Liu, Q., & Li, S. (2002). Word similarity computing based on How-net. Computational Linguistics and Chinese Language Processing, 7, 59–76.Google Scholar
McClelland, J. L. (2009). The place of modeling in cognitive science. Topics in Cognitive Science, 1, 11–28.Google Scholar
McNamara, T. (2005). Semantic priming: Perspectives from memory and word recognition. New York: Psychology Press.Google Scholar
Miller, G. A. (1990). WordNet: An on-line lexical database. International Journal of Lexicography, 3, 235–312.Google Scholar
Munakata, Y., & Pfaffly, J. (2004). Hebbian learning and development. Developmental Science, 7, 141–148.Google Scholar
Paivio, A., & Desrochers, A. (1980). A dual-coding approach to bilingual memory. Canadian Journal of Psychology, 34, 388–399.Google Scholar
Pavlenko, A. (2009). Conceptual representation in the bilingual lexicon and second language vocabulary learning. In Pavlenko, A. (ed.), The bilingual mental lexicon: Interdisciplinary approaches, pp. 125–160. Tonawanda, NY: Multilingual Matters.Google Scholar
Schoonbaert, S., Duyck, W., Brysbaert, M., & Hartsuiker, R. J. (2009). Semantic and translation priming from a first language to a second and back: Making sense of the findings. Memory & Cognition, 37 (5), 569–586.Google Scholar
Schoonbaert, S., Holcomb, P. J., Grainger, J., & Hartsuiker, R. J. (2011). Testing asymmetries in noncognate translation priming: Evidence from RTs and ERPs. Psychophysiology, 48 (1), 74–81.Google Scholar
Segalowitz, N., & de Almeida, R. (2002). Conceptual representation of verbs in bilinguals: Semantic field effects and a second-language performance paradox. Brain and Language, 81 (1), 517–531.Google Scholar
Silberman, Y., Bentin, S., & Miikkulainen, R. (2007). Semantic boost on episodic associations: An empirically-based computational model. Cognitive Science: A Multidisciplinary Journal, 31 (4), 645–671.Google Scholar
Sirosh, J., & Miikkulainen, R. (1994). Cooperative self-organization of afferent and lateral connections in cortical maps. Biological Cybernetics, 71, 66–78.Google Scholar
Spitzer, M. (1999). The mind within the net: Models of learning, thinking, and acting. Cambridge, MA: MIT Press.Google Scholar
Tardif, T., Gelman, S. A., & Xu, F. (1999). Putting the “noun bias” in context: A comparison of English and Mandarin. Child Development, 70, 620–635.Google Scholar
Thomas, M. S. C., & Van Heuven, W. J. B. (2005). Computational models of bilingual comprehension. In Kroll, J. F. & De Groot, A. M. B. (eds.), Handbook of bilingualism: Psycholinguistic approaches, pp. 202–225. New York: Oxford University Press.Google Scholar
Van Hell, J. G., & De Groot, A. M. B. (1998). Conceptual representation in bilingual memory: Effects of concreteness and cognate status in word association. Bilingualism: Language and Cognition, 1 (3), 193–211.Google Scholar
Van Hell, J. G., & Kroll, J. F. (in press). Using electrophysiological measures to track the mapping of words to concepts in the bilingual brain: A focus on translation. In Altarriba, J. & Isurin, L. (eds.), Memory, language, and bilingualism: Theoretical and applied approaches. New York: Cambridge University Press.Google Scholar
Wang, X., & Forster, K. I. (2010). Masked translation priming with semantic categorization: Testing the Sense Model. Bilingualism: Language and Cognition, 13 (3), 327–340.Google Scholar
Xing, H., Shu, H., & Li, P. (2004). The acquisition of Chinese characters: Corpus analyses and connectionist simulations. Journal of Cognitive Science, 5, 1–49.Google Scholar
Xing, H., Shu, H., & Li, P. (2007). A self-organizing model of vocabulary acquisition by elementary school children. Contemporary Linguistics, 9, 193–207. [In Chinese.]Google Scholar
Wu, J. (1997). Language, play and general development for Chinese infant-toddlers. Ph.D. dissertation, University of Colorado at Boulder.Google Scholar
Zhao, X., & Li, P. (2007). Bilingual lexical representation in a self-organizing neural network. In McNamara, D. S. & Trafton, J. G. (eds.), Proceedings of the 29th Annual Cognitive Science Society, pp. 755–760. Nashville, TN.Google Scholar
Zhao, X., & Li, P. (2009). An online database of phnological representation for Mandarin Chinese monosyllables. Behavior Research Methods, 41, 575–583.Google Scholar
Zhao, X., & Li, P. (2010). Bilingual lexical interactions in an unsupervised neural network model. International Journal of Bilingual Education and Bilingualism, 13, 505–524.Google Scholar
Zhao, X., Li, P., & Kohonen, T. (2011a). Contextual self-organizing map: Software for constructing semantic representation. Behavior Research Methods, 43, 77–88.Google Scholar
Zhao, X., Li, P., Liu, Y., Fang, X., & Shu, H. (2011b). Cross-language priming in Chinese–English bilinguals with different second language proficiency levels. In Carlson, L., Hölscher, C. & Shipley, T. (eds.), Proceedings of the 33rd Annual Conference of the Cognitive Science Society, pp. 801–806. Austin, TX: Cognitive Science Society.Google Scholar