Skip to main content
SpringerLink
Log in

Review on Silent Speech Recognition Using EMG Sensors and Voices After Laryngectomy

  • Conference paper
  • First Online:
Electronic Systems and Intelligent Computing

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 686))

Abstract

In this paper, there are four ways of speech rehabilitation techniques after laryngectomy. They are voice prosthesis, esophageal voice, electronic larynx, and silent articulation. After the surgical removal of the larynx, the person cannot speak. After laryngectomy, he/she cannot speak naturally. But using the four techniques mentioned above is helpful to a person without larynx.

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 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 219.99
Price excludes VAT (USA)
  • Durable hardcover 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. Colby G, et al (2009) Sensor subset selection for surface electromyograpy based speech recognition. In: ICASSP, IEEE international conference on acoustics, speech and signal processing, pp 473–476

    Google Scholar 

  2. Atal BS, Chang JJ, Mathews MV, Tukey JW (1978) Inversion of articulatory-to-acoustic transformation in the vocal tract by a computer-sorting technique. J Acoust Soc Am 63(5):1535–1555. https://doi.org/10.1121/1.381848

    Article  Google Scholar 

  3. Noyes JM, Frankish CR (1992) Speech recognition technology for individuals with disabilities. Augment Altern Commun 8(4):297–303. https://doi.org/10.1080/07434619212331276333

    Article  Google Scholar 

  4. Bhowmik T, et al (2017) A comparative study on phonological feature detection from continuous speech with respect to variable corpus size. In: 2016 IEEE Students’ Technol Symp Tech Sym, pp 311–316. https://doi.org/10.1109/TechSym.2016.7872702

  5. Polur PD, Miller GE (2005) Predictive and cepstral coefficients in dysarthric speech 13(4):558–561

    Google Scholar 

  6. Vieira MBM et al (1999) Speech rehabilitation after laryngectomy with the Amatsu tracheoesophageal shunt. Auris Nasus Larynx 26(1):69–77. https://doi.org/10.1016/S0385-8146(98)00065-0

    Article  Google Scholar 

  7. Jou SC, Maier-Hein L, Schultz T, Waibel A (2006) Articulatory feature classification using surface electromyography. In: 2006 IEEE international conference on acoustics speech and signal processing proceedings, Toulouse, France, pp 605–608

    Google Scholar 

  8. Colby G, Heaton JT, Gilmore LD, Sroka J, Deng Y, Cabrera J, Roy S, De Luca CJ, Meltzner GS (2009) Sensor subset selection for surface electromyograpy based speech recognition. In: 2009 IEEE international conference on acoustics, speech and signal processing, Taipei, Taiwan

    Google Scholar 

  9. Meltzner GS et al (2017) Silent speech recognition as an alternative communication device for persons with laryngectomy. IEEE/ACM Trans Audio Speech Lang Process 25(12):2386–2398. https://doi.org/10.1109/TASLP.2017.2740000

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Electronics and Communication Engineering, Aditya College of Engineering and Technology, Surampalem, Andhra Pradesh, India

    Pilla Devi Bhavani & V. Preethi

  2. Accendere Knowledge Management Services Pvt. Ltd, CL Educate Ltd, New Delhi, India

    Durgesh Nandhan

Authors
  1. Pilla Devi Bhavani
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. V. Preethi
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Durgesh Nandhan
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Pilla Devi Bhavani .

Editor information

Editors and Affiliations

  1. School of Computer Engineering, Kalinga Institute of Industrial Technology (KIIT) Deemed to be University, Bhubaneswar, Odisha, India

    Pradeep Kumar Mallick

  2. Department of Electronics and Communication Engineering, National Institute of Technology Arunachal Pradesh, Yupia, Arunachal Pradesh, India

    Preetisudha Meher

  3. Department of Electronics and Communication Engineering, National Institute of Technology Arunachal Pradesh, Yupia, Arunachal Pradesh, India

    Alak Majumder

  4. Department of Electronics and Communication Engineering, National Institute of Technology Rourkela, Rourkela, Odisha, India

    Santos Kumar Das

Rights and permissions

Reprints and permissions

Copyright information

© 2020 The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Bhavani, P.D., Preethi, V., Nandhan, D. (2020). Review on Silent Speech Recognition Using EMG Sensors and Voices After Laryngectomy. In: Mallick, P.K., Meher, P., Majumder, A., Das, S.K. (eds) Electronic Systems and Intelligent Computing. Lecture Notes in Electrical Engineering, vol 686. Springer, Singapore. https://doi.org/10.1007/978-981-15-7031-5_22

Download citation

  • DOI: https://doi.org/10.1007/978-981-15-7031-5_22

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-7030-8

  • Online ISBN: 978-981-15-7031-5

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation