Skip to main content Accessibility help

We use cookies to distinguish you from other users and to provide you with a better experience on our websites. Close this message to accept cookies or find out how to manage your cookie settings.

Close cookie message
×
Hostname: page-component-cd9895bd7-p9bg8 Total loading time: 0 Render date: 2024-12-26T00:27:45.363Z Has data issue: false hasContentIssue false

16 - The Role of Working Memory in Shaping Syntactic Dependency Structures

from Part III - Linguistic Theories and Frameworks

Published online by Cambridge University Press:  08 July 2022

By
Chunshan Xu  and
Haitao Liu
Edited by
John W. Schwieter  and
Zhisheng (Edward) Wen
John W. Schwieter
Affiliation:
Wilfrid Laurier University
Zhisheng (Edward) Wen
Affiliation:
Hong Kong Shue Yan University
Get access

Summary

Dependency syntax holds that the goal of syntactic analysis is to establish all the binary relations between words in a sentence. This process is closely related to working memory. In a sentence, the words between two syntactically related words make for dependency distance, which is an index of sentence comprehension difficulty because, when the two syntactically related words are combined to each other in working memory, the first of them may suffer from memory decay or memory interference caused by the intervening words. Thus, working memory and the least effort principle may dictate a universal tendency for syntactic structures to be organized in such ways as to reduce dependency distance. This tendency has great shaping effect on the patterns of word order in human languages and is potentially able to account for many linguistic universals in language typology. As for the sporadic long dependency structures motivated by communicative needs, specific syntactic patterns may have evolved, utilizing some cognitive mechanisms to lessen the memory load of these long dependencies. Syntactic structures, therefore, are probably the result of self-adaption of a language system to certain external human constraints and motivations, among which working memory is a very important one.

Keywords

working memorydependency distancesyntactic structures
Type
Chapter
Information
The Cambridge Handbook of Working Memory and Language , pp. 343 - 367
Publisher: Cambridge University Press
Print publication year: 2022

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.)

References

Anderson, J. R. (1983). A spreading activation theory of memory. Journal of Verbal Learning and Verbal Behavior, 22(3), 261–295.Google Scholar
Anderson, J. R. (1993). Rules of the mind. Erlbaum.Google Scholar
Anderson, J. R., & Reder, L. M. (1999). The fan effect: New results and new theories. Journal of Experimental Psychology-General, 128, 186–197.CrossRefGoogle Scholar
Baddeley, A. D. (1990). Human memory, theory and practice. Erlbaum.Google Scholar
Baddeley, A. D. (2000a). The episodic buffer: A new component of working memory. Trends in Cognitive Science, 4(11), 417–423.Google Scholar
Baddeley, A. D. (2000b). Short-term and working memory. In Tulving, E., & Craik, F. I. M. (Eds.), The Oxford handbook of memory (pp. 77–92). Oxford University Press.CrossRefGoogle Scholar
Baddeley, A. D., & Hitch, G. (1974). Working memory. In Bower, G. A. (Ed.), Recent advances in learning and motivation (Vol. 8, pp. 647–667). Academic Press.Google Scholar
Bartek, B., Lewis, R. L., Vasishth, S., & Smith, M. R. (2011). In search of on-line locality effects in sentence comprehension. Journal of Experimental Psychology: Learning. Memory and Cognition, 37(5), 178–198.Google ScholarPubMed
Behaghel, O. (1909). Beziehungen zwischen Umfang und Reihenfolge von Satzgliedern. Indogermanische Forschungen, 25, 110–142.Google Scholar
Behaghel, O. (1932). Deutsche Syntax: Eine geschichtliche Darstellung, Bd. 4: Wortstellung; Periodenbau. Winter.Google Scholar
Bresnan, J., Asudeh, A., Toivonen, I., & Wechsler, S. (2015). Lexical functional syntax (2nd ed.). Wiley Blackwell.CrossRefGoogle Scholar
Bresnan, J., Cueni, A., Nikitina, T., & Baayen, H. (2007). Predicting the dative alternation. In Boume, G., Kraemer, I., & Zwarts, J. (Eds.), Cognitive foundations of interpretation (pp. 69–94). Royal Netherlands Academy of Science.Google Scholar
Bybee, J. (2006). From usage to grammar: The mind’s response to repetition. Language, 82(4), 711–733.Google Scholar
Camos, V., & Barrouillet, P. (2011). Factors of working memory development: The time-based resource-sharing model approach. In Barrouillet, P., & Gaillard, V. (Eds.), Cognitive development and working memory (pp. 151–176). Psychology Press.Google ScholarPubMed
Chen, B., Ning, A., Bi, H., & Dunlap, S. (2008). Chinese subject-relative clauses are more difficult to process than the object-relative clauses. Acta Psychologica, 129, 616.CrossRefGoogle Scholar
Choi, H. W. (1999). Optimizing structure in context: Scrambling and information structure. CSLI Publications.Google Scholar
Choi, H. W. (2007). Length and order: A corpus study of Korean dative-accusative construction. Discourse and Cognition, 14(3), 207–227.Google Scholar
Chomsky, N. (1957). Syntactic structures. Mouton.Google Scholar
Chomsky, N. (1988). Language and problems of knowledge: The Managua lectures. MIT Press.Google Scholar
Covington, M. A. (2001). A fundamental algorithm for dependency parsing. In Miller, J. A. & Smith, J. (Eds.), Proceedings of the 39th Annual ACM Southeast Conference, Athens, Georgia, 2001 (pp. 95–102). http://web.stanford.edu/~mjkay/covington.pdfGoogle Scholar
Covington, M. A. (2003). Free-word-order dependency parser in prolog. University of Georgia: Artificial Intelligence Center. www.covingtoninnovations.com/mc/dparser/dparser.pdfGoogle Scholar
Cowan, N. (1995). Attention and memory: An integrated framework. Oxford University Press.Google Scholar
Cowan, N. (1999). An embedded processes model of working memory. In Miyake, A. & Shah, P. (Eds.), Models of working memory: Mechanisms of active maintenance and executive control (pp. 62–101). Cambridge University Press.Google Scholar
Crabbé, B., Gulordava, K., & Merlo, P. (2015). Dependency length minimisation effects in short spans: A large-scale analysis of adjective placement in complex noun phrases. In ACL Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Short Papers) (pp. 477–482). The Association for Computational Linguistics.Google Scholar
den Dikken, M. (2013). Phrase structure grammar. Cambridge University PressGoogle Scholar
Dryer, M. (1992). The Greenbergian word order correlations. Language, 68, 81–138.Google Scholar
Engle, R. W., Cantor, J., & Carullo, J. J. (1992). Individual differences in working memory and comprehension: A test of four hypotheses. Journal of Experimental Psychology: Learning, Memory and Cognition, 5, 972–992.Google Scholar
Eppler, E. (2004). The syntax of German-English code-switching. (Doctoral thesis, University College London).Google Scholar
Ertel, S. (1977). Where do the subjects of the sentences come from? In Rosenberg, S. (Eds.), Sentence production developments in research and theory (pp. 141–168). Lawrence Erlbaum.Google Scholar
Faghiri, P., & Samvelian, P. (2014). Constituent ordering in Persian and the weight factor. In Christopher, P. (Ed.), Empirical issues in syntax and semantics 10 (EISS10). www.cssp.cnrs.fr/eiss10/eiss10_faghiri-and-samvelian.pdf.Google Scholar
Fedorenko, E., Piantadosi, S., & Gibson, E. (2012). Processing relative clauses in supportive contexts. Cognitive Science, 36, 471–497.Google Scholar
Ferrer-i-Cancho, R. (2004). Euclidean distance between syntactically linked words. Physical Review A, 70, 056135.Google Scholar
Ferrer-i-Cancho, R. (2013). Hubiness, length and crossings and their relationships in dependency trees. Glottometrics, 25, 1–21.Google Scholar
Ferrer-i-Cancho, R. (2014). Random crossings in dependency trees. arXiv:1305.4561 [cs.CL]. https://arxiv.org/ftp/arxiv/papers/1305/1305.4561.pdfGoogle Scholar
Ferrer-i-Cancho, R., Gómez-Rodríguez, C., & Esteban, J. L. (2018). Are crossing dependencies really scarce? Physica A, 493, 311–329.CrossRefGoogle Scholar
Frazier, L. (1979). On comprehending sentences: Syntactic parsing strategies. (Doctoral dissertation. University of Connecticut).Google Scholar
Frazier, L. (1985). Syntactic complexity. In Dowty, D. R., Karttunen, L., & Zwicky, A. (Eds.), Natural language parsing: Psychological, computational, and theoretical perspectives (pp. 129–89). Cambridge University Press.Google Scholar
Futrell, R., Mahowald, K., & Gibson, E. (2015). Large-scale evidence for dependency length minimization in 37 languages. Proceedings of the National Academy of Sciences, 112(33), 10336–10341.CrossRefGoogle ScholarPubMed
Futrell, R., Levy, R. P., & Gibson, E. (2020). Dependency locality as an explanatory principle for word order. Language, 96(2), 371–412.Google Scholar
Gibson, E. (1998). Linguistic complexity: Locality of syntactic dependencies. Cognition, 68, 1–76.Google Scholar
Gibson, E. (2000). The dependency locality theory: A distance-based theory of linguistic complexity. In Marantz, A., Miyashita, Y., & O’Neil, W. (Eds.), Image, language, brain (pp. 95–126). MIT Press.Google Scholar
Gibson, E., Piantadosi, S., Brink, K., Bergen, L., Lim, E., & Saxe, R. (2013). A noisy-channel account of cross-linguistic word order variation. Psychological Science, 4(7), 1079–1088.CrossRefGoogle Scholar
Gibson, E., & Wu, I. (2013). Processing Chinese relative clauses in context. Language Cognition and Neuroscience, 28, 125–155.Google Scholar
Gildea, D., & Temperley, D. (2010). Do grammars minimize dependency length? Cognitive Science, 34, 286–310.CrossRefGoogle ScholarPubMed
Givón, T. (2009). The genesis of syntactic complexity. Benjamins.CrossRefGoogle Scholar
Gómez-Rodríguez, C., & Ferrer-i-Cancho, R. (2017). Scarcity of crossing dependencies: A direct outcome of a specific constraint? Physical Review E, 96, 062304.Google Scholar
Grodner, D., & Gibson, E. (2005). Some consequences of the serial nature of linguistic input. Cognitive Science, 29(2), 261–290.Google Scholar
Greenberg, J. H. (1963). Some universals of grammar with particular reference to the order of meaningful elements. In Greenberg, J. H. (Ed.), Universals of language (pp. 40–70). MIT Press.Google Scholar
Haken, H. (1983). Synergetics, an introduction: Nonequilibrium phase transitions and self-organization in physics, chemistry, and biology. Springer-Verlag.Google Scholar
Hawkins, J. A. (1994). A performance theory of order and constituency. Cambridge University Press.Google Scholar
Hiranuma, S. (1999). Syntactic difficulty in English and Japanese: A textual study. UCL Working Papers in Linguistics, 11, 309–322.Google Scholar
Hofmeister, P, Jaeger, T. F., Sag, I. A., Arnon, I., & Snider, N. (2007). Locality and accessibility in wh-questions. In Featherston, S. & Sternefeld, W. (Eds.), Roots: Linguistics in search of its evidential base. Mouton de Gruyter. http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.141.5440&rep=rep1&type=pdfGoogle Scholar
Hofmeister, P,. & Sag, I. A. (2010). Cognitive constraints and island effects. Language, 86, 366–415.Google Scholar
Hsiao, F., & Gibson, E. (2003). Processing relative clauses in Chinese. Cognition, 90, 3–27.Google Scholar
Hudson, R. (1995). Measuring Syntactic Difficulty. http://dickhudson.com/wp-content/uploads/2013/07/Difficulty.pdfGoogle Scholar
Hudson, R. (1998). English grammar. Routledge.Google Scholar
Hudson, R. (2007). Language networks: A new word grammar. Cambridge University Press.Google Scholar
Hudson, R. (2010 ). An introduction to word grammar. Cambridge University Press.Google Scholar
Hurford, J. (2012). The origin of grammar. Oxford University Press.Google Scholar
Husain, H. S., Vasishth, S., & Srinivasan, N. (2014). Strong expectations cancel locality effects: Evidence from Hindi. PLoS ONE, 9(7), e100986.Google Scholar
Jaeger, T. F. (2010). Redundancy and reduction: Speakers manage syntactic information density. Cognitive Psychology, 61, 23–62.CrossRefGoogle ScholarPubMed
Jiang, J. Y., & Liu, H. T. (2015). The effects of sentence length on dependency distance, dependency direction and the implications. Language Sciences, 50, 93–104.CrossRefGoogle Scholar
Jiang, J. Y., & Liu, H. T. (Eds.). (2018). Quantitative analysis of dependency structures. De gruyter Mouton.Google Scholar
Jiang, J. Y., & Ouyang, J. H. (2018). Minimization and probability distribution of dependency distance in the process of second language acquisition. In Jiang, J. Y. & Liu, H. T. (Eds.), Quantitative analysis of dependency structures (pp. 167–190). Walter de Gruyter.Google Scholar
Kauffman, S. (1993). Origins of order: Self organisation and selection in evolution. Oxford University Press.Google Scholar
Köhler, R. (1986). Zur linguistischen Synergetik. Struktur und Dynamik der Lexik. Brockmeyer.Google Scholar
Köhler, R. (2005). Synergetic linguistics. In Köhler, R., Altmann, G., & Piotrowski, R. G. (Eds.). Quantitative linguistics. An international handbook (pp. 760–775). Walter de Gruyter; 2005.Google Scholar
Lakoff, G., & Johnson, M. (2003). Metaphors we live by. University of Chicago Press.Google Scholar
Langacker, R. W. (2008). Cognitive grammar: A basic introduction. Oxford University Press.Google Scholar
Langus, A., & Nespor, M. (2010). Cognitive systems struggling for word order. Cognitive Psychology, 60(4), 291–318.Google Scholar
Levy, R., Fedorenko, E., & Gibson, E. (2013). The syntactic complexity of Russian relative clauses. Journal of Memory and Language, 69, 461–495.Google Scholar
Levy, R., & Keller, F. (2013). Expectation and locality effects in German verb-final structures. Journal of Memory and Language, 68, 199–222.Google Scholar
Li, W. P., & Yan, J. W. (2020). Probability distribution of dependency distance based on a treebank of Japanese EFL learners’ interlanguage. Journal of Quantitative Linguistics, 28(2), 172–186. DOI: 10.1080/09296174.2020.1754611Google Scholar
Li, Z., Zhou, J., & Zhao, H. (2009). Cross language dependency parsing using a bilingual lexicon. Proceedings of the 47th Annual Meeting of the Association for Computational Linguistics and the 4th International Joint Conference on Natural Language Processing of the AFNLP (pp. 55–63). DOI: 10.3115/1687878.1687888Google Scholar
Lin, Y., & Garnsey, S. M. (2010). Animacy and the resolution of temporary ambiguity in relative clause comprehension in Mandarin. In Yamashita, H., Hirose, Y., & Packard, J. (Eds.), Processing and producing head-fifinal structures (pp. 241–275). Springer.Google Scholar
Lin, Y. W. (2011). Locality versus anti-locality effects in Mandarin sentence comprehension. In Jing-Schmidt, Zhuo (Ed.), Proceedings of the 23rd North American conference on Chinese linguistics (NACCL-23) (Vol. 1, pp. 200–214). University of Oregon.Google Scholar
Liu, H. T. (2006). Syntactic parsing based on Dependency Relations. Grkg/Humankybernetik, 47(3), 124–135.Google Scholar
Liu, H. T. (2007). Probability distribution of dependency distance. Glottometrics, 15, 1–12.Google Scholar
Liu, H. T. (2008). Dependency distance as a metric of language comprehension difficulty. Journal of Cognitive Science, 9(2), 159–191.Google Scholar
Liu, H. T. (2018). Language as a human-driven complex adaptive system. Physics of Life Reviews, 26 –27, 149–151.CrossRefGoogle ScholarPubMed
Liu, H. T., Xu, C. S., & Liang, J. Y. (2017). Dependency distance: A new perspective on syntactic patterns in natural languages. Physics of Life Reviews, 21, 171–193.CrossRefGoogle ScholarPubMed
Liu, H. T., Zhao, Y. Y., & Li, W. W. (2009). Chinese syntactic and typological properties based on dependency syntactic treebanks. Poznań Studies in Contemporary Linguistics, 45(4), 509–523.Google Scholar
Lovett, M. C., Reder, L. M., & Lebière, C. (1999). Modeling working memory in a unified architecture: An ACT-R perspective. In Miyake, A. & Shah, P. (Eds.), Models of working memory: Mechanisms of active maintenance and executive control (pp. 135–182). Cambridge University Press.Google Scholar
Lu, Q., & Liu, H. T. (2015). Does dependency distance distribute regularly? The Journal of Zhejiang University (Humanities and Social Science), 4, 63–76 (in Chinese).Google Scholar
Lu, Q., & Liu, H. T. (2016). A quantitative study on the relationship between crossing and distance of human language. Journal of Shanxi University (Philosophy and social Sciences), 39(4), 49–56 (in Chinese).Google Scholar
Lu, Q., Xu, C. S., & Liu, H. T. (2015). The influence of chunking on dependency crossing and distance. Complexity, 21, 33–41.CrossRefGoogle Scholar
McDonald, R., Crammer, K., & Pereira, F. (2005). Online large-margin training of dependency parsers. Proceedings of ACL 2005, 91–98. https://www.aclweb.org/anthology/P05-1012.pdfGoogle Scholar
Mel’čuk, I. (2003). Levels of dependency in linguistic description: Concepts and problems. In Agel, V., Eichinnger, L., Eroms, H. W., Hellwig, P., Herringer, H. J., & Lobin, H. (Eds.), Dependency and valency. An international handbook of contemporary research (Vol. 1, pp. 189–229). De Gruyter.Google Scholar
Nairne, J. (1990). A feature model of immediate memory. Memory & Cognition, 18, 251–269.Google Scholar
Neath, I. (2000). Modeling the effects of irrelevant speech on memory. Psychonomic Bulletin & Review, 7, 403–423.Google Scholar
Nivre, J., & Scholz, M. (2004). Deterministic dependency parsing of English text. Proceedings of the 20th International Conference on Computational Linguistics. www.aclweb.org/anthology/C04-1010.pdfGoogle Scholar
Oberauer, K. (2002). Access to information in working memory: Exploring the focus of attention. Journal of Experimental Psychology: Learning, Memory, and Cognition, 28(3), 411–421.Google Scholar
Oberauer, K., & Lewandowsky, S. (2013). Evidence against decay in verbal working memory. Journal of Experimental Psychology: General, 142(2), 380–411.Google Scholar
Oya, M. (2013). Degree centralities, closeness centralities, and dependency distances of different genres of texts. Selected Papers from the 17th Conference of Pan-Pacific Applied Linguistics; 2013 (pp. 42–53). www.paaljapan.org/conference2012/pdf/006oya.pdfGoogle Scholar
Pollard, C., & Sag, I. A. (1994). Head-driven phrase structure grammar. University of Chicago Press.Google Scholar
Quirk, R., Greenbaum, S., Leech, G., & Svartvik, J. (1972). A grammar of contemporary English. Longman.Google Scholar
Saussure, F. (1959). Course in general linguistics. Philosophical Library.Google Scholar
Temperley, D. (2007). Minimization of dependency length in written English. Cognition, 105, 300–333.Google Scholar
Temperley, D. (2008). Dependency length minimization in natural and artificial languages. Journal of Quantitative Linguistics, 15, 256–282.CrossRefGoogle Scholar
Temperley, D., & Gildea, D. (2018). Minimizing syntactic dependency lengths: Typological/cognitive universal? Annual Review of Linguistics, 4, 67–80.Google Scholar
Tesnière, L. (1959). Eléments de la syntaxe structurale. Klincksieck.Google Scholar
Tily, H. (2010). The role of processing complexity in word order variation and change (Doctoral dissertation, Stanford University).Google Scholar
Ueno, M., & Polinksy, M. (2009). Does headedness affect processing? A new look at the VO–OV contrast. Journal of Linguistics, 45, 675–710.Google Scholar
VanDyke, J. A. (2007). Interference effects from grammatically unavailable constituents during sentence processing. Journal of Experimental Psychology: Learning, Memory and Cognition, 33(2), 407–430.Google Scholar
VanDyke, J. A., & Lewis, R. L. (2003). Distinguishing effects of structure and decay on attachment and repair: A retrieval interference theory of recovery from misanalyzed ambiguities. Journal of Memory and Language, 49(3), 285–316.Google Scholar
Vasishth, S., & Lewis, R. L. (2006). Argument-head distance and processing complexity: Explaining both locality and anti-locality effects. Language, 82(4), 767–794.CrossRefGoogle Scholar
Vergauwe, E., & Cowan, N. (2015). Theories of short-term memory. In Wright, J. D. (Ed.), International encyclopedia of social & behavioral science (2nd ed., vol. 21, pp. 901–908). Elsevier.Google Scholar
Wang, H., & Liu, H. T. (2014). The effect of length and complexity on constituent ordering in written English. Poznań Studies in Contemporary Linguistics, 50(4), 477–494.Google Scholar
Wang, Y. Q., & Liu, H. T. (2017). The effects of genre on dependency distance and dependency direction. Language Sciences, 59, 135–147.CrossRefGoogle Scholar
Wasow, T. (1997). End-weight from the speaker’s perspective. Journal of Psycholinguistic Research, 26, 347–361.Google Scholar
White, K. G. (2012). Dissociation of short-term forgetting from the passage of time. Journal of Experimental Psychology: Learning, Memory and Cognition, 38, 255–259.Google Scholar
Xiang, Y., Agnieszka, F., & Jonas, K. (2019). Dependency length minimization vs. word order constraints: an empirical study on 55 treebanks. In Chen, X. Y. & Ferrer-i-Cancho, R. (Eds.), Proceedings of the First Workshop on Quantitative Syntax (Quasy, SyntaxFest 2019) (pp. 89–97). Association for Computational Linguistics.Google Scholar
Xu, C. S. (2015). The use and the omission of Chinese conjunction “er.” Journal of Shanxi University(Philosophy and Social Sciences Edition), 38(2), 55–61. (in Chinese)Google Scholar
Xu, C. S. (2018). Differences between English subject post-modifiers and object post-modifiers: From the perspective of dependency distance. In Jiang, J. Y., & Liu, H. T. (Eds.), Quantitative analysis of dependency structures (pp. 261–76). Walter de Gruyter.Google Scholar
Xu, C. S., & Liu, H. T. (2015). Can familiarity lessen the effect of locality? A case study of Mandarin Chinese subjects and the following adverbials. Poznań Studies in Contemporary Linguistics, 51(3), 463–486.Google Scholar
Yamada, H., & Matsumoto, Y. (2003). Statistical dependency analysis with support vector machines. In Proceedings of the Eighth International Conference on Parsing Technologies (pp. 195–206). www.aclweb.org/anthology/W03–3023.pdfGoogle Scholar
Yamashita, H., & Chang, F. (2001). Long before short preference in the production of a head-final language. Cognition, 81, B45–B55.Google Scholar
Yan, J. W., & Liu, H. T. (2019). Which annotation scheme is more expedient to measure syntactic difficulty and cognitive demand? In Chen, X. Y., & Ferrer-i-Cancho, R. (Eds.), Proceedings of the First Workshop on Quantitative Syntax (Quasy, SyntaxFest 2019) (pp. 16–24). Association for Computational Linguistics.Google Scholar
Zipf, G. (1949). Human behavior and the principle of least effort: An introduction to human ecology. Hafner.Google Scholar

Save book to Kindle

To save this book to your Kindle, first ensure [email protected] is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

Available formats
×

Save book to Dropbox

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox.

Available formats
×

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

Available formats
×