Hands-Free Wearable Electrolarynx using Linear Predictive Coding Residual Waves and Listening Evaluation

A conventional electrolarynx (EL), which is used by laryngectomees, produces monotonous sound and occupies a user's hand; hence, we developed a hands-free wearable device that improves voice quality. The proposed device estimates individual vocal tract features using linear predictive coding (L...

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Veröffentlicht in:Advanced Biomedical Engineering Jg. 11; S. 68 - 75
Hauptverfasser: Ifukube, Tohru, Takamichi, Shinnosuke, Sekino, Masaki, Lee, Kunhak, Takeuchi, Masaki, Ahn, Jaesol, Yabu, Ken-ichiro, Takaki, Ken, Ueha, Rumi
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Kagoshima Japanese Society for Medical and Biological Engineering 2022
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ISSN:2187-5219, 2187-5219
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Abstract A conventional electrolarynx (EL), which is used by laryngectomees, produces monotonous sound and occupies a user's hand; hence, we developed a hands-free wearable device that improves voice quality. The proposed device estimates individual vocal tract features using linear predictive coding (LPC) and generates sound vibrations using an LPC inverse filter. Additionally, we reproduced the vibration sound using a transducer and amplified the first harmonic frequency and the second one. We conducted an objective experiment to compare the spectra of natural voice, a conventional EL, and the proposed device. We also conducted a subjective experiment in which we asked healthy subjects to listen to and evaluate the conventional EL and the proposed device. The results of the objective experiment demonstrated that our model was characterized by two formant peaks that were similar to the conventional EL and the natural voice. The results of the subjective experiment demonstrated that our model was more powerful and clearer than the conventional EL. These findings indicate that the voice of our device is spectrally close to human voice and gives the audience a more powerful and clearer sound.
AbstractList A conventional electrolarynx (EL), which is used by laryngectomees, produces monotonous sound and occupies a user’s hand; hence, we developed a hands-free wearable device that improves voice quality. The proposed device estimates individual vocal tract features using linear predictive coding (LPC) and generates sound vibrations using an LPC inverse filter. Additionally, we reproduced the vibration sound using a transducer and amplified the first harmonic frequency and the second one. We conducted an objective experiment to compare the spectra of natural voice, a conventional EL, and the proposed device. We also conducted a subjective experiment in which we asked healthy subjects to listen to and evaluate the conventional EL and the proposed device. The results of the objective experiment demonstrated that our model was characterized by two formant peaks that were similar to the conventional EL and the natural voice. The results of the subjective experiment demonstrated that our model was more powerful and clearer than the conventional EL. These findings indicate that the voice of our device is spectrally close to human voice and gives the audience a more powerful and clearer sound.
ArticleNumber 11_68
Author Takeuchi, Masaki
Takaki, Ken
Ifukube, Tohru
Ueha, Rumi
Takamichi, Shinnosuke
Lee, Kunhak
Ahn, Jaesol
Sekino, Masaki
Yabu, Ken-ichiro
Author_xml – sequence: 1
  fullname: Ifukube, Tohru
  organization: Research Center for Advanced Science and Technology, The University of Tokyo
– sequence: 1
  fullname: Takamichi, Shinnosuke
  organization: Department of Information Science and Technology, The University of Tokyo
– sequence: 1
  fullname: Sekino, Masaki
  organization: Department of Bioengineering, The University of Tokyo
– sequence: 1
  fullname: Lee, Kunhak
  organization: Faculty of Mechanical Engineering, The University of Tokyo
– sequence: 1
  fullname: Takeuchi, Masaki
  organization: Graduate School of Engineering, The University of Tokyo
– sequence: 1
  fullname: Ahn, Jaesol
  organization: Faculty of Information and Communication Engineering, The University of Tokyo
– sequence: 1
  fullname: Yabu, Ken-ichiro
  organization: Research Center for Advanced Science and Technology, The University of Tokyo
– sequence: 1
  fullname: Takaki, Ken
  organization: Graduate School of Engineering, The University of Tokyo
– sequence: 1
  fullname: Ueha, Rumi
  organization: Swallowing Center, The University of Tokyo Hospital, The University of Tokyo
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Cites_doi 10.1109/ICASSP.2014.6854451
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10.1109/AEEICB.2018.8480968
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References 20. Xiao K, Wang S, Wan M, Wu L: Radiated noise suppression for electrolarynx speech based on multiband time-domain amplitude modulation. IEEE/ACM Trans Audio Speech Lang Process. 26(9), 1585–1593. 2018.
29. Kishimoto M, Toda T, Doi H, Sakti S, Nakamura S: Model training using parallel data with mismatched pause positions in statistical esophageal speech enhancement. Proc of the International Conference on Signal Processing, Kuala Lumpur, pp. 590–594, 2012.
33. Takeuchi M, Ahn J, Matsufuji K, Lee K, Ogasawara Y, Takaki K, Ifukube T, Yabu K, Takamichi S, Ueha R, Sekino M, Onodera H: Development of a hands-free electrolarynx that obtains a voice close to human using the LPC residual wave. The papers of technical meeting on magnetics, IEE Japan 2020(73–79), 7–12, 2020.
31. Speech Resources Consortium (NII-SRC): ATR 503 sentences. Retrieved from http://research.nii.ac.jp/src/en/ATR503.html. Accessed on October 17, 2021.
12. Tanaka K, Toda T, Neubig G, Sakti S, Nakamura S: Direct F0 control of an electrolarynx based on statistical excitation feature prediction and its evaluation through simulation. INTERSPEECH, Singapore, pp. 31–35, 2014.
21. Malathi P, Suresh DGR, Moorthi DM: Enhancement of electrolaryngeal speech using frequency auditory masking and GMM based voice conversion. Proc of the 4th International Conference on Advances in Electrical, Electronics, Information, Communication and Bio-Informatics, Tamilnadu, pp. 1–4, 2018.
14. Tanaka K, Toda T, Neubig G, Sakti S, Nakamura S: An evaluation of excitation feature prediction in a hybrid approach to electrolaryngeal speech enhancement. Proc of the IEEE International Conference on Acoustics, Speech and Signal Processing, Florence, pp. 4488–4492, 2014.
16. Liu H, Zhao Q, Wan M, Supin W: Enhancement of electrolarynx speech based on auditory masking. IEEE Trans Biomed Eng. 53(5), 865–874, 2006.
6. Heaton JT, Goldstein EA, Kobler JB, Zeitels SM, Randolph GW, Walsh MJ, Gooey JE, Hillman RE: Surface electromyographic activity in total laryngectomy patients following laryngeal nerve transfer to neck strap muscles. Ann Otol Rhinol Laryngol. 113(9), 754–764, 2004.
1. Uemi N, Ifukube T, Takahashi M, Matsushima J: Design of a new electrolarynx having a pitch control function. Proc of the IEEE International Workshop on Robot and Human Communication, Nagoya, pp. 198–203, 1994.
30. Werner S, Hoffmann R: Pronunciation variant selection for spontaneous speech synthesis - A summary of experimental results. Proc of the International Conference on Speech Prosody, Dresden, pp. 857–860, 2006.
13. Doi H, Toda T, Nakamura K, Saruwatari H, Shikano K: Alaryngeal speech enhancement based on one-to-many eigenvoice conversion. IEEE Trans Audio Speech Lang Process. 22(1), 172–183, 2014.
25. Morikawa M: [Acoustic measurement and calibration] Onkyokeisoku to kyaribreesyon (in Japanese). J Acoust Soc Jpn. 74(6), 351–356, 2020.
8. Kubert HL, Stepp CE, Zeitels SM, Gooey JE, Walsh MJ, Prakash SR, Hillman RE, Heaton JT: Electromyographic control of a hands-free electrolarynx using neck strap muscles. J Commun Disord. 42(3), 211–225, 2009.
26. Imaizumi S: [Alaryngeal Voicing Methods and Their Inherent Voice Quality] Daiyohasseihou to sono seishitsu (in Japanese). Jpn J Logopedics Phoniatrics. 24, 204–210, 1983.
5. Goldstein EA, Heaton JT, Kobler JB, Stanley GB, Hillman RE: Design and implementation of a hands-free electrolarynx device controlled by neck strap muscle electromyographic activity. Proc of the International IEEE/EMBS Conference on Neural Engineering, Capri, pp. 169–172, 2003.
15. Tanaka K, Toda T, Neubig G, Sakti S, Nakamura S: An enhanced electrolarynx with automatic fundamental frequency control based on statistical prediction. Proc of the 17th International ACM SIGACCESS Conference on Computers and Accessibility, Lisbon, pp. 435–436, 2015.
9. Nagle KF, Heaton JT: Perceived naturalness of electrolaryngeal speech produced using sEMG-controlled vs. manual pitch modulation. Proc of the Annual Conference of the International Speech Communication Association, INTERSPEECH, San Francisco, pp. 238–242, 2016.
7. Stepp CE, Heaton JT, Rolland RG, Hillman RE: Neck and face surface electromyography for prosthetic voice control after total laryngectomy. IEEE Trans Neural Syst Rehabil Eng. 17(2), 146–155, 2009.
3. Hashiba M, Sugai Y, T. Ifukube: OS3–2 commercialization of the multi-functional electro-larynx YOUR TONE II and it's further development for hands-free operation (OS3: Rehabilitation Devices I). Proc of the Asian Pacific Conference on Biomechanics: Emerging Science and Technology in Biomechanics, Sapporo, pp. 81, 2015.
18. Li S, Wan MX, Wang SP: Multi-band spectral subtraction method for electrolarynx speech enhancement. Algorithms. 2(1), 550–564, 2009.
28. Dall R, Yamagishi J, King S: Rating naturalness in speech Synthesis: The effect of style and expectation. Proc of the International Conference on Speech Prosody, Dublin, pp. 1012–1016, 2014.
2. Hashiba M, Sugai Y, Izumi T, Ino S, Ifukube T: Development of a wearable electro-larynx for laryngectomees and its evaluation. Proc of the Annual International Conference of the IEEE Engineering in Medicine and Biology, Lyon, pp. 5267–5270, 2007.
22. Ifukube T: Design of the voice typewriter, pp. 22–24, CQ publisher, 1983.
19. Bhat RM, Singh JB, Lehana PK: Investigations of the effect of nonlinearly generated excitations on the quality of the synthesized alaryngeal speech. Indian J Sci Technol. 10(18), 1–12, 2017.
24. Boersma P, van Heuven V: Speak and unSpeak with Praat. Glot Int. 5(9–10), 341–347, 2001.
11. Chadha A, Savardekar B, Padhya J: Analysis of a modern voice morphing approach using Gaussian mixture models for laryngectomees. Int J Comput Appl. 49(21), 25–30, 2012.
32. Doi H: Augmented speech production beyond physical constraints using statistical voice conversion: Alaryngeal speech enhancement and singing voice quality control, Ph.D. dissertation, 2013. https://library.naist.jp/mylimedio/dllimedio/showpdf2.cgi/DLPDFR009998_P1-128, (Accessed on July 25, 2021).
27. Nieboer GLJ, de Graaf T, Schutte HK: Esophageal voice quality judgements by means of the semantic differential. J Phonetics. 16(4), 417–436, 1988.
23. Hei T, Tanaka Y, Mizumachi M, Nakatoh Y, Matsui K: Study of natural-voice-like vibration sound for electrolarynx. Proc of the 2nd International Conference on Intelligent Systems and Image Processing, Kitakyushu, pp. 159–162, 2014.
4. Matsui K, Kimura K, Nakatoh Y, Kato YO: Development of electrolarynx with hands-free prosody control. Proc of the 8th ISCA Workshop on Speech Synthesis (SSW), Barcelona, Vol. 121, pp. 273–277, 2013.
17. Liu H, Ng ML: Electrolarynx in voice rehabilitation. Auris Nasus Larynx. 34(3), 327–332, 2007.
10. Nakamura K, Toda T, Saruwatari H, Shikano K: Speaking-aid systems using GMM-based voice conversion for electrolaryngeal speech. Speech Commun. 54(1), 134–146, 2012.
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References_xml – reference: 17. Liu H, Ng ML: Electrolarynx in voice rehabilitation. Auris Nasus Larynx. 34(3), 327–332, 2007.
– reference: 11. Chadha A, Savardekar B, Padhya J: Analysis of a modern voice morphing approach using Gaussian mixture models for laryngectomees. Int J Comput Appl. 49(21), 25–30, 2012.
– reference: 24. Boersma P, van Heuven V: Speak and unSpeak with Praat. Glot Int. 5(9–10), 341–347, 2001.
– reference: 2. Hashiba M, Sugai Y, Izumi T, Ino S, Ifukube T: Development of a wearable electro-larynx for laryngectomees and its evaluation. Proc of the Annual International Conference of the IEEE Engineering in Medicine and Biology, Lyon, pp. 5267–5270, 2007.
– reference: 15. Tanaka K, Toda T, Neubig G, Sakti S, Nakamura S: An enhanced electrolarynx with automatic fundamental frequency control based on statistical prediction. Proc of the 17th International ACM SIGACCESS Conference on Computers and Accessibility, Lisbon, pp. 435–436, 2015.
– reference: 3. Hashiba M, Sugai Y, T. Ifukube: OS3–2 commercialization of the multi-functional electro-larynx YOUR TONE II and it's further development for hands-free operation (OS3: Rehabilitation Devices I). Proc of the Asian Pacific Conference on Biomechanics: Emerging Science and Technology in Biomechanics, Sapporo, pp. 81, 2015.
– reference: 12. Tanaka K, Toda T, Neubig G, Sakti S, Nakamura S: Direct F0 control of an electrolarynx based on statistical excitation feature prediction and its evaluation through simulation. INTERSPEECH, Singapore, pp. 31–35, 2014.
– reference: 23. Hei T, Tanaka Y, Mizumachi M, Nakatoh Y, Matsui K: Study of natural-voice-like vibration sound for electrolarynx. Proc of the 2nd International Conference on Intelligent Systems and Image Processing, Kitakyushu, pp. 159–162, 2014.
– reference: 30. Werner S, Hoffmann R: Pronunciation variant selection for spontaneous speech synthesis - A summary of experimental results. Proc of the International Conference on Speech Prosody, Dresden, pp. 857–860, 2006.
– reference: 22. Ifukube T: Design of the voice typewriter, pp. 22–24, CQ publisher, 1983.
– reference: 33. Takeuchi M, Ahn J, Matsufuji K, Lee K, Ogasawara Y, Takaki K, Ifukube T, Yabu K, Takamichi S, Ueha R, Sekino M, Onodera H: Development of a hands-free electrolarynx that obtains a voice close to human using the LPC residual wave. The papers of technical meeting on magnetics, IEE Japan 2020(73–79), 7–12, 2020.
– reference: 5. Goldstein EA, Heaton JT, Kobler JB, Stanley GB, Hillman RE: Design and implementation of a hands-free electrolarynx device controlled by neck strap muscle electromyographic activity. Proc of the International IEEE/EMBS Conference on Neural Engineering, Capri, pp. 169–172, 2003.
– reference: 19. Bhat RM, Singh JB, Lehana PK: Investigations of the effect of nonlinearly generated excitations on the quality of the synthesized alaryngeal speech. Indian J Sci Technol. 10(18), 1–12, 2017.
– reference: 26. Imaizumi S: [Alaryngeal Voicing Methods and Their Inherent Voice Quality] Daiyohasseihou to sono seishitsu (in Japanese). Jpn J Logopedics Phoniatrics. 24, 204–210, 1983.
– reference: 4. Matsui K, Kimura K, Nakatoh Y, Kato YO: Development of electrolarynx with hands-free prosody control. Proc of the 8th ISCA Workshop on Speech Synthesis (SSW), Barcelona, Vol. 121, pp. 273–277, 2013.
– reference: 28. Dall R, Yamagishi J, King S: Rating naturalness in speech Synthesis: The effect of style and expectation. Proc of the International Conference on Speech Prosody, Dublin, pp. 1012–1016, 2014.
– reference: 27. Nieboer GLJ, de Graaf T, Schutte HK: Esophageal voice quality judgements by means of the semantic differential. J Phonetics. 16(4), 417–436, 1988.
– reference: 31. Speech Resources Consortium (NII-SRC): ATR 503 sentences. Retrieved from http://research.nii.ac.jp/src/en/ATR503.html. Accessed on October 17, 2021.
– reference: 10. Nakamura K, Toda T, Saruwatari H, Shikano K: Speaking-aid systems using GMM-based voice conversion for electrolaryngeal speech. Speech Commun. 54(1), 134–146, 2012.
– reference: 7. Stepp CE, Heaton JT, Rolland RG, Hillman RE: Neck and face surface electromyography for prosthetic voice control after total laryngectomy. IEEE Trans Neural Syst Rehabil Eng. 17(2), 146–155, 2009.
– reference: 6. Heaton JT, Goldstein EA, Kobler JB, Zeitels SM, Randolph GW, Walsh MJ, Gooey JE, Hillman RE: Surface electromyographic activity in total laryngectomy patients following laryngeal nerve transfer to neck strap muscles. Ann Otol Rhinol Laryngol. 113(9), 754–764, 2004.
– reference: 29. Kishimoto M, Toda T, Doi H, Sakti S, Nakamura S: Model training using parallel data with mismatched pause positions in statistical esophageal speech enhancement. Proc of the International Conference on Signal Processing, Kuala Lumpur, pp. 590–594, 2012.
– reference: 16. Liu H, Zhao Q, Wan M, Supin W: Enhancement of electrolarynx speech based on auditory masking. IEEE Trans Biomed Eng. 53(5), 865–874, 2006.
– reference: 9. Nagle KF, Heaton JT: Perceived naturalness of electrolaryngeal speech produced using sEMG-controlled vs. manual pitch modulation. Proc of the Annual Conference of the International Speech Communication Association, INTERSPEECH, San Francisco, pp. 238–242, 2016.
– reference: 8. Kubert HL, Stepp CE, Zeitels SM, Gooey JE, Walsh MJ, Prakash SR, Hillman RE, Heaton JT: Electromyographic control of a hands-free electrolarynx using neck strap muscles. J Commun Disord. 42(3), 211–225, 2009.
– reference: 1. Uemi N, Ifukube T, Takahashi M, Matsushima J: Design of a new electrolarynx having a pitch control function. Proc of the IEEE International Workshop on Robot and Human Communication, Nagoya, pp. 198–203, 1994.
– reference: 14. Tanaka K, Toda T, Neubig G, Sakti S, Nakamura S: An evaluation of excitation feature prediction in a hybrid approach to electrolaryngeal speech enhancement. Proc of the IEEE International Conference on Acoustics, Speech and Signal Processing, Florence, pp. 4488–4492, 2014.
– reference: 13. Doi H, Toda T, Nakamura K, Saruwatari H, Shikano K: Alaryngeal speech enhancement based on one-to-many eigenvoice conversion. IEEE Trans Audio Speech Lang Process. 22(1), 172–183, 2014.
– reference: 18. Li S, Wan MX, Wang SP: Multi-band spectral subtraction method for electrolarynx speech enhancement. Algorithms. 2(1), 550–564, 2009.
– reference: 25. Morikawa M: [Acoustic measurement and calibration] Onkyokeisoku to kyaribreesyon (in Japanese). J Acoust Soc Jpn. 74(6), 351–356, 2020.
– reference: 21. Malathi P, Suresh DGR, Moorthi DM: Enhancement of electrolaryngeal speech using frequency auditory masking and GMM based voice conversion. Proc of the 4th International Conference on Advances in Electrical, Electronics, Information, Communication and Bio-Informatics, Tamilnadu, pp. 1–4, 2018.
– reference: 32. Doi H: Augmented speech production beyond physical constraints using statistical voice conversion: Alaryngeal speech enhancement and singing voice quality control, Ph.D. dissertation, 2013. https://library.naist.jp/mylimedio/dllimedio/showpdf2.cgi/DLPDFR009998_P1-128, (Accessed on July 25, 2021).
– reference: 20. Xiao K, Wang S, Wan M, Wu L: Radiated noise suppression for electrolarynx speech based on multiband time-domain amplitude modulation. IEEE/ACM Trans Audio Speech Lang Process. 26(9), 1585–1593. 2018.
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Snippet A conventional electrolarynx (EL), which is used by laryngectomees, produces monotonous sound and occupies a user's hand; hence, we developed a hands-free...
A conventional electrolarynx (EL), which is used by laryngectomees, produces monotonous sound and occupies a user’s hand; hence, we developed a hands-free...
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StartPage 68
SubjectTerms Coding
Experiments
signal processing
Sound
Sound reproduction
transducer
Vibrations
Voice
Wearable technology
welfare device
Title Hands-Free Wearable Electrolarynx using Linear Predictive Coding Residual Waves and Listening Evaluation
URI https://www.jstage.jst.go.jp/article/abe/11/0/11_11_68/_article/-char/en
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Volume 11
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