Skip to main content
SpringerLink
Log in

Digital Wah-Wah Guitar Effect Controlled by Mouth Movements

  • Conference paper
  • First Online:
Computer Vision and Graphics (ICCVG 2022)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 598))

Included in the following conference series:

  • 251 Accesses

Abstract

The wah-wah is a guitar effect used to modulate the sound while playing. This is an unusual effect in that the guitar player, having his hands on instrument, controls it in real time with the foot. The digital equivalent proposed in this paper transfers this control to mouth movements by capturing an image from a computer camera and then applying computer vision algorithms. The paper analyzes the applicability and studies the effectiveness of using mouth movement to control a wah-wah type guitar effect.

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 149.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 199.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Silva, G.C., Smyth, T., Lyons, M.: A novel face-tracking mouth controller and its application to interacting with bioacoustic models. In: Proceedings of the 2004 Conference on New Interfaces for Musical Expression, pp. 169–172 (2004)

    Google Scholar 

  2. Mu-Chun, S., Chin-Yen, Y., Yi-Zeng, H., Shih-Chieh, L., Pa-Chun, W.: An image-based mouth switch for people with severe disabilities. Recent Patent. Comput. Sci. 5(1), 66–71 (2012)

    Google Scholar 

  3. Gomez, J., Ceballos, A., Prieto, F., Redarce, T.: Mouth gesture and voice command based robot command interface. In: 2009 IEEE International Conference on Robotics and Automation, pp. 333–338 (2009). https://doi.org/10.1109/ROBOT.2009.5152858

  4. Corey, J., Benson, D.H.: Audio Production and Critical Listening: Technical Ear Training, 2nd edn, Routledge (2016)

    Google Scholar 

  5. Kartynnik, Y., Ablavatski, A., Grishchenko, I., Grundmann, M.: Real-time Facial Surface Geometry from Monocular Video on Mobile GPUs, arXiv preprint arXiv:1907.06724 (2019)

  6. King, D.E.: Dlib-ml: A machine learning toolkit. J. Mach. Learn. Res. 10, 1755–1758 (2009)

    Google Scholar 

  7. Kavitha, R., Subha, P., Srinivasan, R., Kavitha, M.: Implementing OpenCV and Dlib Open-Source library for detection of driver’s fatigue. In: Raj, J.S., Kamel, K., Lafata, P. (eds.) Innovative Data Communication Technologies and Application. Lecture Notes on Data Engineering and Communications Technologies, vol. 96. Springer, Singapore (2022). https://doi.org/10.1007/978-981-16-7167-8_26

  8. Babu, A., Nair, S., Sreekumar, K.: Driver’s drowsiness detection system using Dlib HOG. In: Karuppusamy, P., Perikos, I., García Márquez, F.P. (eds.) Ubiquitous Intelligent Systems. Smart Innovation, Systems and Technologies, vol. 243. Springer, Singapore (2022). https://doi.org/10.1007/978-981-16-3675-2_16

  9. Elmahmudi, A., Ugail, H.: A framework for facial age progression and regression using exemplar face templates. Vis. Comput. 37, 2023–2038 (2021). https://doi.org/10.1007/s00371-020-01960-z

    Article  Google Scholar 

  10. Mandol, S., Mia, S., Ahsan, S.M.M.: Real time liveness detection and face recognition with OpenCV and deep learning. In: 2021 5th International Conference on Electrical Information and Communication Technology (EICT), pp. 1–6 (2021). https://doi.org/10.1109/EICT54103.2021.9733685

  11. Jácome, J., Gomes, A., Costa, W.L., Figueiredo. L.S., Abreu, J., Porciuncula, L., Brant, P.K., Alves, L.E.M., Correia, W.F.M., Teichrieb, V., Quintino, J.P., da Silva, F.Q.B., Santos, A.L.M., Pinho, H.S.: Parallax engine: Head controlled motion parallax using notebooks’ RGB camera. In: Symposium on Virtual and Augmented Reality, pp. 137–146 (2021). https://doi.org/10.1145/3488162.3488218

  12. Boyko, N., Basystiuk, O., Shakhovska, N.: Performance evaluation and comparison of software for face recognition, based on Dlib and Opencv library. In: 2018 IEEE Second International Conference on Data Stream Mining & Processing (DSMP), pp. 478–482 (2018). https://doi.org/10.1109/DSMP.2018.8478556

  13. Soukupová, T., Cech, J.: Real-time eye blink detection using facial landmarks. In: 21st Computer Vision Winter Workshop, pp. 3–5. Rimske Toplice, Slovenia (2016)

    Google Scholar 

  14. Małecki, K., Nowosielski, A., Forczmański, P.: Multispectral data acquisition in the assessment of driver’s fatigue. In: Mikulski J. (ed.) Smart Solutions in Today’s Transport. TST 2017. Communications in Computer and Information Science, vol. 715. Springer, Cham (2017)

    Google Scholar 

  15. Nowosielski, A., Forczmański, P.: Touchless typing with head movements captured in thermal spectrum. Pattern Anal. Appl. 22(3), 841–855 (2019)

    Article  MathSciNet  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Faculty of Computer Science and Information Technology, West Pomeranian University of Technology, Szczecin, Żołnierska 52 Str., 71-210, Szczecin, Poland

    Adam Nowosielski & Przemysław Reginia

Authors
  1. Adam Nowosielski
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Przemysław Reginia
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Adam Nowosielski .

Editor information

Editors and Affiliations

  1. Institute of Information Technology, Warsaw University of Life Sciences—SGGW, Warsaw, Poland

    Leszek J. Chmielewski

  2. Institute of Information Technology, Warsaw University of Life Sciences—SGGW, Warsaw, Poland

    Arkadiusz Orłowski

Rights and permissions

Reprints and permissions

Copyright information

© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Nowosielski, A., Reginia, P. (2023). Digital Wah-Wah Guitar Effect Controlled by Mouth Movements. In: Chmielewski, L.J., Orłowski, A. (eds) Computer Vision and Graphics. ICCVG 2022. Lecture Notes in Networks and Systems, vol 598. Springer, Cham. https://doi.org/10.1007/978-3-031-22025-8_3

Download citation

Publish with us

Policies and ethics

Search

Navigation