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Türkçede Konuşma Kalıplarının İşlemlenmesi: Maskelenmiş Çağrıştırma Çalışması

Year 2020, Volume: 31 Issue: 2, 207 - 230, 30.12.2020

Dilek Göymen Mehmet Aygüneş

https://doi.org/10.18492/dad.750788

Abstract

Alanyazında birçok çalışma kalıp ifadelerin diğer yapılardan daha hızlı işlemlendiği göstermesine rağmen, bu işlemleme avantajının kaynağı üzerine oldukça sınırlı sayıda çalışma bulunmaktadır. Bütüncül Yaklaşım, bu avantajı kalıp ifadelerin parçalarına ayrıştırılmadan bir bütün olarak işlemlenmesi ile açıklarken, kalıp ifadelerin diğer yapılar gibi parçaları aracılığıyla işlemlendiğini savunan Dağıtılmış Simgeleme, bunu ifadeleri oluşturan sözcüklerin zihinsel bir bağ geliştirerek birbirini etkinleştirmesi ile açıklamaktadır. Maskelenmiş çağrıştırma yöntemiyle Türkçe konuşma kalıplarının işlemlenmesinin incelendiği bu çalışmada, kalıp ifadelerin işlemlenmesinde bu görüşlerden hangisinin geçerli olduğu sorgulanmıştır. Tepki süreleri incelendiğinde, Dağıtılmış Simgeleme görüşünün öne sürdüğü gibi konuşma kalıpları ile kalıplaşmamış ifadeler arasında anlamlı bir fark tespit edilememiştir. Ayrıca, anlamsal açıdan saydam olan konuşma kalıplarının saydam olmayanlara göre daha hızlı işlemlendiği tespit edilirken, katkısız eylem içermenin sadece saydam olmayan yapılar içerisinde anlamlı fark yarattığı görülmüştür.

Keywords

Konuşma kalıpları kalıp ifadelerin işlemlenmesi anlamsal saydamlık katkısız eylemler maskelenmiş çağrıştırma

Project Number

SDP-2019-34179

References

  • Aksan, Y., Aksan, M., Koltuksuz, A., Sezer, T., Mersinli, Ü., Demirhan, U. U., Yılmazer, H., Kurtoğlu, Ö., Atasoy, G., Öz, S., & Yıldız, İ. (2012). Construction of the Turkish National Corpus (TNC). In N. Calzolari, K. Choukri, T. Declerck et al (Eds.), Proceedings of the 12th International Conference on Language Resources and Evaluation (pp. 3223-3227). İstanbul: LREC 2012.
  • Akşehirli, S. (2013). Türkçede et- Katkısız Eyleminin Sözlüksel İşlevleri. Turkish Studies - International Periodicals for The Languages, Literature and History of Turkish or Turkic, 8(9), 481-494.
  • Arıca-Akkök, E., & Uzun, İ.P. (2018). Metaphor Processing in Turkish: An Eye-Movement Study. Mersin Üniversitesi Dil ve Edebiyat Dergisi, 15 (1), 105-124.
  • Arnon, I., & Cohen Priva, U. (2014). Time and again: The changing effect of word and multiword frequency on phonetic duration for highly frequent sequences. The Mental Lexicon, 9(3), 377–400.
  • Berk, G, Erden, B., & Güngör, T. (2018). Turkish verbal multiword expressions corpus, 26th Signal Processing and Communications Aplications Conference, 64, 1-4.
  • Bonferroni, C. E. (1936). Teoria statistica delle classi e calcolo delle probabilita. Pubblicazioni del R Istituto Superiore di Scienze Economiche e Commerciali di Firenze, 8, 3–62.
  • Cangır, H., Büyükkantarcıoğlu, N. S. ve Durrant, P. (2017). Investigating collocational priming in Turkish. Journal of Language and Linguistic Studies, 13(2), 465-486.
  • Carrol, G., & Conklin, K. (2020). Is All Formulaic Language Created Equal? Unpacking the Processing Advantage for Different Types of Formulaic Sequences. Language and Speech, 63(1), 95–122.
  • Conklin, K., & Schmitt, N. (2008). Formulaic Sequences: Are They Processed More Quickly than Nonformulaic Language by Native and Nonnative Speakers? Applied Linguistics, 29 (1), 72–89.
  • Erman, B., & Warren, B. (2000). The idiom principle and the open choice principle. Text, 20(1), 29-62.
  • 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.
  • Greenhouse, S. W., & Geisser, S. (1959). On methods in the analysis of profile data. Psychometrika, 24, 95–112.
  • Haselow, A. (2018). Language change from a psycholinguistic perspective: The long-term effects of frequency on language processing. Language Sciences, 68, 56–77.
  • Hunston, S. (2002). Corpora in applied linguistics. Cambridge: Cambridge University Press.
  • Isobe, Y. (2011). Representation and Processing of Formulaic Sequences in L2 Mental Lexicon: How Do Japanese EFL Learners Process Multi-word Expressions? JACET Kansai Journal, 13, 38–49.
  • Jeong, H., & Jiang, N. (2019). Representation and processing of lexical bundles: Evidence from word monitoring. System, 188-198.
  • Kapatsinski, V., & J. Radicke. (2009). Frequency and the emergence of prefabs: Evidence from monitoring. In R. Corrigan, E. Moravcsik, H. Ouali, & K. Wheatley (Eds). Formulaic Language. Vol. II: Acquisition, loss, psychological reality, functional explanations (pp. 499-520). Amsterdam: John Benjamins.
  • Keuleers, E., & Brysbaert, M. (2010). Wuggy: A multilingual pseudoword generator. Behavior Research Methods, 42(3), 627-633.
  • Lamb, S. (1999). Pathways of the brain: The neurocognitive basis of language. Amsterdam: Benjamins.
  • Ortaçtepe, D. (2013). Formulaic language and conceptual socialization: The route to becoming nativelike in L2. System, 41, 852–865.
  • Pérez-Llantada, C. (2014). Formulaic language in L1 and L2 expert academic writing: Convergent and divergent usage. Journal of English for Academic Purposes, 14, 84-94.
  • Qin, J. (2014). Use of formulaic bundles by non-native English graduate writers and published authors in applied linguistics. System, 42, 220-231.
  • Sinclair, J. (1991). Corpus, concordance, collocation. Oxford: Oxford University Press.
  • Siyanova, A., & Schmitt, N. (2008). L2 learner production and processing of collocation: A multi-study perspective. Canadian Modern Language Review, 64(3), 429–458.
  • Siyanova-Chanturia, A., Conklin, K., & Schmitt, N. (2011). Adding more fuel to the fire: An eye-tracking study of idiom processing by native and non-native speakers. Second Language Research, 27(2), 251–272.
  • Siyanova-Chanturia, A., Conklin, K., Caffarra, S., Kaan, E., & Heuven, W. J. B. (2017). Representation and processing of multi-word expressions in the brain. Brain and Language 175, 111–122.
  • Siyanova-Chanturia, A., & Martinez, R. (2014), ' The Idiom Principle Revisited'. Applied Linguistics, 36(5): 549–69.
  • Siyanova-Chanturia, A. (2015). On the‘holistic’nature of formulaic language. Corpus Linguistics and Ling. Theory, 11(2), 285–301.
  • Sosa, A. V. ve J. MacFarlane. (2002). Evidence for frequency-based constituents in the mental lexicon: Collocations involving the word of. Brain and Language 83(2), 227–236.
  • Tremblay, A., & Baayen, R.H. (2010). Holistic processing of regular fourword sequences: A behavioral and ERP study of the effects of structure, frequency, and probability on immediate free recall. In D. Wood (Ed.), Perspectives on formulaic language: Acquisition and communication (pp. 151–173). London and New York: Continuum
  • Underwood, G., Schmitt, N., & Galpin, A. (2004). The eyes have it: An eye-movement study into the processing of formulaic sequences. In N. Schmitt (Ed.), Formulaic sequences (pp. 153-172). Philadelphia: John Benjamins.
  • Uygun, S., & Gürel, A. (2016). Processing morphology in L2 Turkish: The effects of morphological richness in the L1. In A. Gürel (Ed.), Second Language Acquisition of Turkish (pp. 251-279). Amsterdam: John Benjamins Publishing.
  • Wray, A. (2002). Formulaic language and the lexicon. Cambridge: Cambridge University Press.
  • Wray, A. (2008). Formulaic language: pushing the boundaries. Oxford Applied Linguistics. Oxford: Oxford University Press.
  • Wood, D. (2015). Fundamentals of formulaic language: An introduction. London: Bloomsbury.

The Processing of Speech Formulas on Turkish: A Masked Priming Study

Year 2020, Volume: 31 Issue: 2, 207 - 230, 30.12.2020

Dilek Göymen Mehmet Aygüneş

https://doi.org/10.18492/dad.750788

Abstract

Studies have indicated that formulaic sequences are processed significantly faster than newly created phrases; however, the source of this processing advantage has not been sufficiently investigated in the literature. The Holistic Approach justifies this processing advantage for formulaic sequences with the argument that they are processed and stored as single units without being decomposed into their constituents. On the contrary, Distributed Representation argues against holistic processing. It proposes instead that formulaic sequences are processed through their parts as in novel non-formulaic phrases. Their constituents form a mutual association in the sense that the mental activation of a component part activates the other, thus leading to faster processing. The present study reports findings from a masked priming experiment investigating Turkish speech formulas' online processing in native processing. Results show that speech formulas and their matched novel phrases are processed similarly, as evidenced by no significant difference in reaction times. These findings support Distributed Representation in the processing of formulaic sequences. Results also suggest that non-transparent formulas are processed more slowly than transparent ones.

Keywords

speech formulas processing of formulaic sequences semantic transparency light verbs masked priming

Supporting Institution

Scientific Research Projects (BAP) Coordination Unit of Istanbul University

Project Number

SDP-2019-34179

Thanks

The authors wish to thank Prof. Dr. Ayşe Gürel for her valuable criticisms and suggestions. All errors belong to authors.

References

  • Aksan, Y., Aksan, M., Koltuksuz, A., Sezer, T., Mersinli, Ü., Demirhan, U. U., Yılmazer, H., Kurtoğlu, Ö., Atasoy, G., Öz, S., & Yıldız, İ. (2012). Construction of the Turkish National Corpus (TNC). In N. Calzolari, K. Choukri, T. Declerck et al (Eds.), Proceedings of the 12th International Conference on Language Resources and Evaluation (pp. 3223-3227). İstanbul: LREC 2012.
  • Akşehirli, S. (2013). Türkçede et- Katkısız Eyleminin Sözlüksel İşlevleri. Turkish Studies - International Periodicals for The Languages, Literature and History of Turkish or Turkic, 8(9), 481-494.
  • Arıca-Akkök, E., & Uzun, İ.P. (2018). Metaphor Processing in Turkish: An Eye-Movement Study. Mersin Üniversitesi Dil ve Edebiyat Dergisi, 15 (1), 105-124.
  • Arnon, I., & Cohen Priva, U. (2014). Time and again: The changing effect of word and multiword frequency on phonetic duration for highly frequent sequences. The Mental Lexicon, 9(3), 377–400.
  • Berk, G, Erden, B., & Güngör, T. (2018). Turkish verbal multiword expressions corpus, 26th Signal Processing and Communications Aplications Conference, 64, 1-4.
  • Bonferroni, C. E. (1936). Teoria statistica delle classi e calcolo delle probabilita. Pubblicazioni del R Istituto Superiore di Scienze Economiche e Commerciali di Firenze, 8, 3–62.
  • Cangır, H., Büyükkantarcıoğlu, N. S. ve Durrant, P. (2017). Investigating collocational priming in Turkish. Journal of Language and Linguistic Studies, 13(2), 465-486.
  • Carrol, G., & Conklin, K. (2020). Is All Formulaic Language Created Equal? Unpacking the Processing Advantage for Different Types of Formulaic Sequences. Language and Speech, 63(1), 95–122.
  • Conklin, K., & Schmitt, N. (2008). Formulaic Sequences: Are They Processed More Quickly than Nonformulaic Language by Native and Nonnative Speakers? Applied Linguistics, 29 (1), 72–89.
  • Erman, B., & Warren, B. (2000). The idiom principle and the open choice principle. Text, 20(1), 29-62.
  • 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.
  • Greenhouse, S. W., & Geisser, S. (1959). On methods in the analysis of profile data. Psychometrika, 24, 95–112.
  • Haselow, A. (2018). Language change from a psycholinguistic perspective: The long-term effects of frequency on language processing. Language Sciences, 68, 56–77.
  • Hunston, S. (2002). Corpora in applied linguistics. Cambridge: Cambridge University Press.
  • Isobe, Y. (2011). Representation and Processing of Formulaic Sequences in L2 Mental Lexicon: How Do Japanese EFL Learners Process Multi-word Expressions? JACET Kansai Journal, 13, 38–49.
  • Jeong, H., & Jiang, N. (2019). Representation and processing of lexical bundles: Evidence from word monitoring. System, 188-198.
  • Kapatsinski, V., & J. Radicke. (2009). Frequency and the emergence of prefabs: Evidence from monitoring. In R. Corrigan, E. Moravcsik, H. Ouali, & K. Wheatley (Eds). Formulaic Language. Vol. II: Acquisition, loss, psychological reality, functional explanations (pp. 499-520). Amsterdam: John Benjamins.
  • Keuleers, E., & Brysbaert, M. (2010). Wuggy: A multilingual pseudoword generator. Behavior Research Methods, 42(3), 627-633.
  • Lamb, S. (1999). Pathways of the brain: The neurocognitive basis of language. Amsterdam: Benjamins.
  • Ortaçtepe, D. (2013). Formulaic language and conceptual socialization: The route to becoming nativelike in L2. System, 41, 852–865.
  • Pérez-Llantada, C. (2014). Formulaic language in L1 and L2 expert academic writing: Convergent and divergent usage. Journal of English for Academic Purposes, 14, 84-94.
  • Qin, J. (2014). Use of formulaic bundles by non-native English graduate writers and published authors in applied linguistics. System, 42, 220-231.
  • Sinclair, J. (1991). Corpus, concordance, collocation. Oxford: Oxford University Press.
  • Siyanova, A., & Schmitt, N. (2008). L2 learner production and processing of collocation: A multi-study perspective. Canadian Modern Language Review, 64(3), 429–458.
  • Siyanova-Chanturia, A., Conklin, K., & Schmitt, N. (2011). Adding more fuel to the fire: An eye-tracking study of idiom processing by native and non-native speakers. Second Language Research, 27(2), 251–272.
  • Siyanova-Chanturia, A., Conklin, K., Caffarra, S., Kaan, E., & Heuven, W. J. B. (2017). Representation and processing of multi-word expressions in the brain. Brain and Language 175, 111–122.
  • Siyanova-Chanturia, A., & Martinez, R. (2014), ' The Idiom Principle Revisited'. Applied Linguistics, 36(5): 549–69.
  • Siyanova-Chanturia, A. (2015). On the‘holistic’nature of formulaic language. Corpus Linguistics and Ling. Theory, 11(2), 285–301.
  • Sosa, A. V. ve J. MacFarlane. (2002). Evidence for frequency-based constituents in the mental lexicon: Collocations involving the word of. Brain and Language 83(2), 227–236.
  • Tremblay, A., & Baayen, R.H. (2010). Holistic processing of regular fourword sequences: A behavioral and ERP study of the effects of structure, frequency, and probability on immediate free recall. In D. Wood (Ed.), Perspectives on formulaic language: Acquisition and communication (pp. 151–173). London and New York: Continuum
  • Underwood, G., Schmitt, N., & Galpin, A. (2004). The eyes have it: An eye-movement study into the processing of formulaic sequences. In N. Schmitt (Ed.), Formulaic sequences (pp. 153-172). Philadelphia: John Benjamins.
  • Uygun, S., & Gürel, A. (2016). Processing morphology in L2 Turkish: The effects of morphological richness in the L1. In A. Gürel (Ed.), Second Language Acquisition of Turkish (pp. 251-279). Amsterdam: John Benjamins Publishing.
  • Wray, A. (2002). Formulaic language and the lexicon. Cambridge: Cambridge University Press.
  • Wray, A. (2008). Formulaic language: pushing the boundaries. Oxford Applied Linguistics. Oxford: Oxford University Press.
  • Wood, D. (2015). Fundamentals of formulaic language: An introduction. London: Bloomsbury.
There are 35 citations in total.

Details

Primary Language English
Journal Section Research Articles
Authors

Dilek Göymen

Mehmet Aygüneş

Project Number SDP-2019-34179
Publication Date December 30, 2020
Published in Issue Year 2020 Volume: 31 Issue: 2

Cite

APA Göymen, D., & Aygüneş, M. (2020). The Processing of Speech Formulas on Turkish: A Masked Priming Study. Dilbilim Araştırmaları Dergisi, 31(2), 207-230. https://doi.org/10.18492/dad.750788

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Journal DOI: 10.18492/dad