The LS Model (Lexicon-Syllabary Model)

  • Bernd J. Kröger
  • Trevor Bekolay


This section presents an approach for modeling speech processing and speech learning. Parts of this simulation model are implemented in the STAA approach, with other parts already in the NEF. The model described here comprises cognitive and sensory-motor components of speech production and perception. Additionally, we simulate the emergence of the mental lexicon and the mental syllabary using babbling and imitation training.


Mental lexicon Mental syllabary Articulation Speaking rate Neural oscillator 


  1. Birkholz P, Jackel D (2004) Influence of temporal discretization schemes on formant frequencies and bandwidths in time domain simulations of the vocal tract system. In: Proceedings of Interspeech. ICSLP, Jeju, pp 1125–1128Google Scholar
  2. Birkholz P, Kröger BJ (2006) Vocal tract model adaptation using magnetic resonance imaging. Proceedings of the 7th International Seminar on Speech Production (Belo Horizonte, Brazil) pp. 493–500Google Scholar
  3. Birkholz P, Jackel D, Kröger BJ (2006) Construction and control of a three-dimensional vocal tract model. Proceedings of the International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2006) (Toulouse, France) pp. 873–876Google Scholar
  4. Birkholz P, Jackel D, Kröger BJ (2007) Simulation of losses due to turbulence in the time-varying vocal system. IEEE Trans Audio Speech Lang Process 15:1218–1225CrossRefGoogle Scholar
  5. Cao M, Li A, Fang Q, Kaufmann E, Kröger BJ (2014) Interconnected growing self-organizing maps for auditory and semantic acquisition modeling. Front Psychol 5:236PubMedPubMedCentralGoogle Scholar
  6. Eliasmith C (2013) How to build a brain. Oxford University Press, OxfordCrossRefGoogle Scholar
  7. Eliasmith C, Stewart TC, Choo X, Bekolay T, DeWolf T, Tan Y (2012) A large-scale model of the functioning brain. Science 338:1202–1205CrossRefGoogle Scholar
  8. Kröger BJ (1997) Zur artikulatorischen Realisierung von Phonationstypen mittels eines selbstschwingenden Glottismodells. Sprache-Stimme-Gehör 21:102–105Google Scholar
  9. Kröger BJ, Birkholz P (2007) A gesture-based concept for speech movement control in articulatory speech synthesis. In: Esposito A, Faundez-Zanuy M, Keller E, Marinaro M (eds) Verbal and nonverbal communication behaviours, LNAI 4775. Springer Verlag, Berlin, Heidelberg, pp 174–189CrossRefGoogle Scholar
  10. Kröger BJ, Birkholz P, Neuschaefer-Rube C (2011) Towards an articulation-based developmental robotics approach for word processing in face-to-face communication. PALADYN J Behav Robot 2:82–93Google Scholar
  11. Kröger BJ, Cao M (2015) The emergence of phonetic-phonological features in a biologically inspired model of speech processing. J Phon 53:88–100CrossRefGoogle Scholar
  12. Kröger BJ, Kannampuzha J (2008) A neurofunctional model of speech production including aspects of auditory and audio-visual speech perception. Proceedings of the International Conference on Audio-Visual Speech Processing 2008, Moreton Island, Queensland, Australia. pp. 83–88Google Scholar
  13. Kröger BJ, Kannampuzha J, Neuschaefer-Rube C (2009) Towards a neurocomputational model of speech production and perception. Speech Comm 51:793–809CrossRefGoogle Scholar
  14. Kröger BJ, Bekolay T, Eliasmith C (2014a) Modeling speech production using the Neural Engineering Framework. Proceedings of CogInfoCom 2014 (Vetri sul Mare, Italy) pp. 203–208 (ISBN: 978-1-4799-7279-1) and IEEE Xplore Digital Library.
  15. Kröger BJ, Kannampuzha J, Kaufmann E (2014b) Associative learning and self-organization as basic principles for simulating speech acquisition, speech production, and speech perception. EPJ Nonlinear Biomedical Physics 2:2CrossRefGoogle Scholar
  16. Kröger BJ, Bekolay T, Blouw P (2016a) Modeling motor planning in speech processing using the Neural Engineering Framework. In: Jokisch O (ed) Studientexte zur Sprachkommunikation: Elektronische Sprachsignalverarbeitung 2016. TUDpress, Dresden, pp 15–22Google Scholar
  17. Kröger BJ, Crawford E, Bekolay T, Eliasmith C (2016b) Modeling interactions between speech production and perception: speech error detection at semantic and phonological levels and the inner speech loop. Front Comput Neurosci 10:51CrossRefGoogle Scholar
  18. Markram H (2006) The blue brain project. Nat Rev Neurosci 7:153–160CrossRefGoogle Scholar
  19. Senft V, Stewart TC, Bekolay T, Eliasmith C, Kröger BJ (2016) Reduction of dopamine in basal ganglia and its effects on syllable sequencing in speech: a computer simulation study. Basal Ganglia 6:7–17CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Bernd J. Kröger
    • 1
  • Trevor Bekolay
    • 2
  1. 1.Department of Phoniatrics, Pedaudiology and Communications DisordersRWTH Aachen UniversityAachenGermany
  2. 2.Applied Brain ResearchWaterlooCanada

Personalised recommendations