SMILLE for Portuguese: Annotation and Analysis of Grammatical Structures in a Pedagogical Context

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11122)


In Second Language Acquisition (SLA), the exposure of learners to authentic material is an important learning step, but the use of raw text may pose problems, because the information that the learner should be focusing on may be overlooked. In this paper, we present SMILLE for Portuguese, a system for detecting pedagogically relevant grammatical structures in raw texts. SMILLE’s rules for recognizing grammatical structures were evaluated in random sentences from three different genres, achieving an overall precision of 84%. The automatic recognition of pedagogically relevant grammatical structures can help teachers and course coordinators to better inform the choice of texts to be used in language courses, while also allowing for the analysis of grammar profiles for SLA. As a case study, we used SMILLE to analyze pedagogical material used in a Portuguese as foreign language course and to observe how the predominance of grammatical content in the texts is related to the described grammatical focus of the language levels.


Second Language Acquisition Grammatical structures Natural Language Processing Grammatical parsing for Portuguese 


  1. 1.
    Azab, M., Salama, A., Oflazer, K., Shima, H., Araki, J., Mitamura, T.: An english reading tool as a NLP showcase. In: The Companion Volume of the Proceedings of IJCNLP 2013: System Demonstrations, pp. 5–8. Asian Federation of Natural Language Processing, Nagoya, Japan, October 2013.
  2. 2.
    Azab, M., Salama, A., Oflazer, K., Shima, H., Araki, J., Mitamura, T.: An NLP-based reading tool for aiding non-native english readers. Recent Advances in Natural Language Processing, p. 41 (2013)Google Scholar
  3. 3.
    Brown, J., Eskenazi, M.: Retrieval of authentic documents for reader-specific lexical practice. In: InSTIL/ICALL Symposium 2004 (2004)Google Scholar
  4. 4.
    Chinkina, M., Kannan, M., Meurers, D.: Online information retrieval for language learning. In: ACL 2016, p. 7 (2016)Google Scholar
  5. 5.
    Cross, J.: Noticing’in sla: Is it a valid concept. TESL-EJ 6(3), 1–9 (2002)MathSciNetGoogle Scholar
  6. 6.
    Doughty, C.: Second language instruction does make a difference. Stud. Second Lang. Acquisition 13(04), 431–469 (1991)CrossRefGoogle Scholar
  7. 7.
    Manning, C.D., Surdeanu, M., Bauer, J., Finkel, J., Bethard, S.J., McClosky, D.: The Stanford CoreNLP natural language processing toolkit. In: Association for Computational Linguistics (ACL) System Demonstrations, pp. 55–60 (2014).
  8. 8.
    Marujo, L., et al.: Porting reap to european portuguese. In: SLaTE, pp. 69–72 (2009)Google Scholar
  9. 9.
    Meurers, D., et al.: Enhancing authentic web pages for language learners. In: Proceedings of the NAACL HLT 2010 Fifth Workshop on Innovative Use of NLP for Building Educational Applications, pp. 10–18. Association for Computational Linguistics (2010)Google Scholar
  10. 10.
    Plonsky, L., Ziegler, N.: The CALL-SLA interface: Insights from a second-order synthesis (2016)Google Scholar
  11. 11.
    Reinders, H.: Towards a definition of intake in second language acquisition (2012)Google Scholar
  12. 12.
    Schmidt, R.: The role of consciousness in second language learning1. Appl. Linguistics 11(2), 129–158 (1990)CrossRefGoogle Scholar
  13. 13.
    Schmidt, R.: Attention, awareness, and individual differences in language learning. Perspect. Indiv. Characteristics Foreign Lang. Educ. 6, 27 (2012)Google Scholar
  14. 14.
    Simard, D.: Differential effects of textual enhancement formats on intake. System 37(1), 124–135 (2009)CrossRefGoogle Scholar
  15. 15.
    Smith, M.S.: Input enhancement in instructed sla. Stud. Second Lang. Acquisition 15(02), 165–179 (1993)CrossRefGoogle Scholar
  16. 16.
    Smith, M.S., Truscott, J.: Explaining input enhancement: a mogul perspective. Int. Rev. Appl. Linguistics Lang. Teach. 52(3), 253–281 (2014)Google Scholar
  17. 17.
    Tiedemann, J.: Finding alternative translations in a large corpus of movie subtitle. In: International Conference on Language Resources and Evaluation (2016)Google Scholar
  18. 18.
    Truscott, J.: Noticing in second language acquisition: a critical review. Second Lang. Res. 14(2), 103–135 (1998)CrossRefGoogle Scholar
  19. 19.
    Verhelst, N., Van Avermaet, P., Takala, S., Figueras, N., North, B.: Common European Framework of Reference for Languages: Learning, Teaching, Assessment. Cambridge University Press, Cambridge (2009)Google Scholar
  20. 20.
    Zilio, L., Fairon, C.: Adaptive system for language learning. In: 2017 IEEE 17th International Conference on Advanced Learning Technologies (ICALT), pp. 47–49. IEEE (2017)Google Scholar
  21. 21.
    Zilio, L., Wilkens, R., Fairon, C.: Passport: a dependency parsing model for portugueseGoogle Scholar
  22. 22.
    Zilio, L., Wilkens, R., Fairon, C.: Enhancing grammatical structures in web-based texts. In: Proceedings of the 25th EUROCALL, pp. 839–846, Accepted, 2017Google Scholar
  23. 23.
    Zilio, L., Wilkens, R., Fairon, C.: Using NLP for enhancing second language acquisition. In: Proceedings of Recent Advances in Natural Language Processing, pp. 839–846 (2017)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  1. 1.Centre de traitement automatique du langage – CENTALUniversité catholique de Louvain (UCL)Louvain-la-NeuveBelgium

Personalised recommendations