Skip to main content
SpringerLink
Log in

A Novel Method for Constructing 3D Geometric Articulatory Models

  • Published:
Journal of Signal Processing Systems Aims and scope Submit manuscript

Abstract

This study describes a novel method of constructing a geometric articulatory model based on magnetic resonance imaging data by taking the physiological boundaries of speech apparatus into account. Two improvements have been made to the modeling process: i) Images taken from different viewpoints are combined to improve the accuracy of outline annotation. ii) Speech organs’ meshes are modeled with reference to the anatomical structures. Both qualitative and quantitative evaluations indicated that the proposed method surpasses the conventional method. Based on the meshes of the speech organs associated with different articulations, the linear component analysis was used to extract the control parameters. Each speech organ can be described using three control parameters or fewer. After the reconstruction, the average error between model and real data was less than 1.0 mm. This is also the first effort made to construct a 3D vocal tract model based on Chinese MRI data. It will facilitate the theoretical study and practical use in Chinese-speech-production related issues.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
Figure 7

Similar content being viewed by others

References

  1. Guenther, F. H. (1994). A neural network model of speech acquisition and motor equivalent speech production. Biological Cybernetics, 72, 43–53.

    Article  Google Scholar 

  2. Guenther, F. H. (1995). Speech sound acquisition, coarticulation, and rate effects in a neural network model of speech production. Psychological Review, 102, 594–621.

    Article  Google Scholar 

  3. Guenther, F. H. (2006). Cortical interactions underlying the production of speech sounds. Journal of Communication Disorders, 39, 350–365.

    Article  Google Scholar 

  4. Fang, Q., et al. (2008). Investigation of the functional relationship of tongue muscles for the control of a physioloigcal articulatory model. in The 8th national conference of Phonetics. Beijing, China.

  5. Fang, Q., Nishikido, A., & Dang, J. (2009). Feedforward control of a 3D physiological articulatory model for vowel production. Tsinghua Science and Technology, 14(5), 617–622.

  6. Dang, J., & Honda, K. (2004). Construction and control of a physiological articulatory model. Journal of the Acoustical Society of America, 115(2), 853–870.

    Article  Google Scholar 

  7. Birkholz, P., Jackèl, D., & Kröger, B. J. (2007). Simulation of losses due to turbulence in the time-varying vocal system. IEEE Transactions on Audio, Speech and Language Processing, 15(4), 1218–1226.

    Article  Google Scholar 

  8. Perrier, P., Ma, L. & Payan, Y. (2005). Modeling the production of VCV sequences via the inversion if a biomechanical model of the tongue. in INTERSPEECH 2005. Lisbon, Portugal.

  9. Mermelstein, P. (1973). Articulatory model for the study of speech production. Journal of the Acoustical Society of America, 53, 1070–1082.

    Article  Google Scholar 

  10. Maeda, S. (1990). Compensatory articulation during speech: evidence from the analysis and synthesis of vocal-tract shapes using an articulatory model. In W. J. Hardcastle and A. Marchal (Eds.), Speech Production and Speech Modelling, Kluwer Academic, Dordrecht, 131–149.

  11. Badin, P., & Serrurier, A. (2006). Three-dimensional modeling of speech organs: articulatory data and models. Transactions on Technical Committee of Psychological and Physiological Acoustics, 365(H-2006-77), 421–426.

    Google Scholar 

  12. Engwall, O. (2003). Combining MRI, EMA and EPG measurements in a three-dimensional tongue model. Speech Communication, 41, 303–329.

    Article  Google Scholar 

  13. Rubin, P., & Baer, T. (1981). An articulatory synthesizer for perception research. Journal of the Acoustical Society of America, 70(2), 321–328.

    Article  Google Scholar 

  14. Birkholz, P., Jackèl, D., & Kröger, B. J. (2006). Construction and control of a three-dimensional vocal tract model, in ICASSP. p. 873–876.

  15. Beautemps, D., Badin, P., & Bailly, G. (2001). Linear degrees of freedom in speech production: analysis of cineradio- and labio-film data and articulatory-acoustic modeling. Journal of the Acoustical Society of America, 109(5), 2165–2180.

    Article  Google Scholar 

  16. Badin, P., et al. (1998). A threedimensional linear articulatory model based on MRI data, in The 3rd ESCA/COCOSDA International Workshop on Speech Synthesis. p. 249–254.

  17. Badin, P., et al. (2002). Three-dimensional linear articulatory modeling of tongue, lips and face, based on MRI and video images. Journal of Phonetics, 30(3), 533–553.

    Article  Google Scholar 

  18. Masaki, S., Tiede, M. K., et al. (1996). MRI-based speech production study using a synchronized sampling method. Journal of Acoustic Society Japan (E), 20, 375–379.

    Article  Google Scholar 

  19. Beautemps, D., et al. (1996). Evaluation of an articulatory-acoustic model based on a reference subject, in The 4th ISSP.

Download references

Acknowledgments

This work was supported by the National Natural Science-Foundation of China (No. 61175016,61304250), Key Fund projects of 61233009 and financial support from CASS Innovation Project “teaching pronunciation models for speech research”.

Author information

Authors and Affiliations

  1. School of Computer Software, Tianjin University, Tianjin, China

    Jianguo Wei & Wenhuan Lu

  2. Phonetics Lab., Institute of Linguistics, Chinese Academy of Social Sciences, Beijing, China

    Qiang Fang

  3. Tianjin Key Lab. of Cognitive Computing and Application, Tianjin University, Tianjin, China

    Jianguo Wei, Jie Liu, Jianwu Dang & Kiyoshi Honda

  4. School of Information Science, Japan Advanced Institute of Science and Technology, Ishikawa, Japan

    Jianwu Dang

Authors
  1. Jianguo Wei
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jie Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Qiang Fang
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Wenhuan Lu
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Jianwu Dang
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Kiyoshi Honda
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Qiang Fang.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Wei, J., Liu, J., Fang, Q. et al. A Novel Method for Constructing 3D Geometric Articulatory Models. J Sign Process Syst 82, 295–302 (2016). https://doi.org/10.1007/s11265-015-1002-8

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11265-015-1002-8

Keywords

Search

Navigation