Representation and Exploring the Semantic Organization of Bangla Word in the Mental Lexicon: Evidence from Cross-Modal Priming Experiments and Vector Space Model

  • Rakesh Dutta
  • Biswapati Jana
  • Mukta Majumder
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 470)


In this paper, our primary intention is to determine the access mechanism and representation of semantically related Bangla word pairs in the mental lexicon. We conduct a visual priming experiment and user-annotated experiment over a number of native speakers in Bangla. After analyzing the response time and rate of errors, we observed that the priming is triggered to the semantically related word pairs in the mental lexicon. On the other hand, the response time data thus collected is used to evaluate on vector space model for finding the complete behavior of semantically related Bangla word pairs in the mental lexicon. The visual word recognition and interactive methods are to ensure with our result that the semantic priming may trigger or regulate the processing of word pairs at an early stage.


Semantic priming Mental lexicon Response time Degree of priming Vector space model 


  1. 1.
    R. Frost, K.I. Forster, A. Deutsch, What can we learn from the morphology of Hebrew? A masked-priming investigation of morphological representation. J. Exp. Psychol. Learn. Mem. Cogn. 23, 829–856 (1997)CrossRefGoogle Scholar
  2. 2.
    J. Grainger, P. Cole, J. Segui, Masked morphological priming in visual word recognition. J. Mem. Lang. 30, 370–384 (1991)Google Scholar
  3. 3.
    E. Drews, P. Zwitserlood, Morphological and orthographic similarity in visual word recognition. J. Exp. Psychol. Hum. Percept. Perform. 21, 1098–1116 (1995)CrossRefGoogle Scholar
  4. 4.
    M. Taft, Morphological decomposition and the reverse base frequency effect. Q. J. Exp. Psychol. 57A, 745–765 (2004)Google Scholar
  5. 5.
    J.H. Neely, Semantic priming effects in visual word recognition: a selective review of current findings and theories, in Basic Processes in Reading: Visual Word Recognition, ed. by D. Besner, G.W. Humphreys. (Erlbaum, Hillsdale, NJ), pp. 264–336 (1991)Google Scholar
  6. 6.
    M. Lucas, Semantic priming without association: a meta-analytic review. Psychon. Bull. Rev. 7, 618–630 (2000)CrossRefGoogle Scholar
  7. 7.
    D.E. Meyer, R.W. Schvaneveldt, Facilitation in recognizing pairs of words: evidence of a dependence between retrieval operation. J. Exp. Psychol. 90, 227–234 (1971)CrossRefGoogle Scholar
  8. 8.
    L. Postman, G. Keppel, Norms of Word Associations (Academic Press, New York, 1970)Google Scholar
  9. 9.
    I. Fischler, Semantic facilitation without association in a lexical decision task. Mem. Cogn. 5, 335–339 (1977)CrossRefGoogle Scholar
  10. 10.
    J.A. Fodor, Modularity of Mind (MIT Press, Cambridge, MA, 1983)Google Scholar
  11. 11.
    K. McRae, V. de Sa, M.S. Seidenberg, On the nature and scope of featural representations of word meaning. J. Exp. Psychol. Gen. 126, 99–130 (1997)CrossRefGoogle Scholar
  12. 12.
    R. Ratcliff, Methods for dealing with reaction time outliers. Psychol. Bull. 114(3), 510 (1993)Google Scholar
  13. 13.
    J.L. Fleiss, B. Levin, M.C. Paik, The measurement of interrater agreement. Stat. Methods Rates Prop. 2, 212–236 (1981)Google Scholar
  14. 14.
    J. Mitchell, M. Lapata, Vector-based models of semantic composition, in Proceedings of ACL-08: HLT, pp. 236–244 (2008)Google Scholar

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© Springer Nature Singapore Pte Ltd. 2017

Authors and Affiliations

  1. 1.Department of Computer ScienceHijli CollegeKharagpurIndia
  2. 2.Department of Computer ScienceVidyasagar UniversityMidnaporeIndia
  3. 3.Department of Computer Science and applicationUniversity of North BengalDarjeelingIndia

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