Research on spectrum feature of speech processing strategy for cochlear implant_Journal of Biomedical Engineering

Authors：

CHEN Yousheng ,  WANG Jian , CHEN Weifang , GUAN Mingxiang

ShenZhen Institute of Information Technology, Shenzhen, Guangdong 518100, P.R.China;

Corresponding author：

WANG Jian, Email: wangj01@sziit.com.cn

Keywords：

cochlear implant; speech processing strategy; energy intensity; formant

DOI：

10.7507/1001-5515.201702020

Video：

Export PDF Favorites Scan Get Citation

Abstract Full text Figures/Tables Video References Cited by

Cochlear implant (CI) in present Chinese environment will lose pitch information and result in low speech recognition. In order to research Chinese feature-based speech processing strategy for cochlear implant contrapuntally and to improve the speech recognition for CI recipients, we improve the CI front-end signal acquisition platform and research the signal features. Our search includes the waveform, spectrogram, energy intensity, pitch and formant parameters for different speech processing strategies of cochlear implant. Features in two kinds of speech processing strategies are analyzed and extracted for the study of parameter characteristics. Therefore, the proposed aim of this paper is to extend the research on Chinese-based CI speech processing strategy.

Citation： CHEN Yousheng, WANG Jian, CHEN Weifang, GUAN Mingxiang. Research on spectrum feature of speech processing strategy for cochlear implant. Journal of Biomedical Engineering, 2017, 34(5): 760-766. doi: 10.7507/1001-5515.201702020 Copy

1.	Van Immerseel L, Peeters S, Dykmans R, et al. SPAIDE: A real-time research platform for the Clarion CII/90K cochlear implant. EURASIP J Appl Signal Processing, 2005(18): 3060-3068.
2.	Ali H, Lobo A P, Loizou P C. Design and evaluation of a personal digital assistant-based research platform for cochlear implants. IEEE Trans Biomed Eng, 2013, 60(11): 3060-3073.
3.	Shane P, Murat T, Nasser K. Real-time implementation of cochlear implant speech processing pipeline on smartphones//36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Chicago, 2014: 886-889.
4.	Joshua S S, Chandra S T, Leslie M C. Developing a flexible SPEAR3-based psychophysical research platform for testing cochlear implant users. Durham, NC: Duke University, 2008.
5.	Fatemeh S, Taher M, Nasser K. A multi-band environment-adaptive approach to noise suppression for cochlear implant//36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Chicago, 2014: 1699-1702.
6.	Mirzahasanloo T, Gopalakrishna V, Kehtarnavaz N, et al. Adding real-time noise suppression capability to the cochlear implant PDA research platform//34th Annual International Conference of the IEEE EMBS, San Diego, 2012: 2271-2274.
7.	Mirzahasanloo T S, Kehtarnavaz N, Panahi I. Adding quiet and music detection capabilities to FDA-approved cochlear implant research platform//8th International Symposium on Image and Signal Processing and Analysis, Trieste, 2013: 399-403.
8.	陈又圣, 宫琴. 基于双 TP 型麦克风的电子耳蜗前端指向性语音增强系统的研制. 仪器仪表学报, 2010, 31(9): 1952-19580.
9.	Chen Yousheng, Gong Qin. Broadband beamforming compensation algorithm in CI front-end acquisition, Biomed Eng Online, 2013: 18.
10.	Chen Yousheng, Gong Qin. Head influence platform for cochlear implant//World Congress on Medical Physics and Biomedical Engineering, Beijing, 2013, 39: 1468-1471.
11.	Skinner M W, Holder L K, Whitford L A. Speech recognition with the nucleus 24 SPEAK, ACE, and CIS speech coding strategies in newly implanted adults. Ear Hear, 2002, 23(3): 207-223.
12.	Psarros C E, Plant K L, Lee K, et al. Conversion from the SPEAK to the ACE strategy in children using the Nucleus 24 cochlear implant system: Speech perception and speech production outcomes. Ear Hear, 2002, 23(1, S): 18S-27S.
13.	Ziese M, Stutzel A, von Specht H. Speech understanding with the CIS and the n-of-m strategy in the MED-EL COMBI 40+ system. Orl-J Oto-Rhino-Laryngol, 2000, 62(6): 321-329.
14.	Buechner A, Frohne C, Boyle P. A high rate n-of-m speech processing strategy for the first generation Clarion cochlear implant. Int J Audiol, 2009, 48(12): 868-875.

1. Van Immerseel L, Peeters S, Dykmans R, et al. SPAIDE: A real-time research platform for the Clarion CII/90K cochlear implant. EURASIP J Appl Signal Processing, 2005(18): 3060-3068.
2. Ali H, Lobo A P, Loizou P C. Design and evaluation of a personal digital assistant-based research platform for cochlear implants. IEEE Trans Biomed Eng, 2013, 60(11): 3060-3073.
3. Shane P, Murat T, Nasser K. Real-time implementation of cochlear implant speech processing pipeline on smartphones//36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Chicago, 2014: 886-889.
4. Joshua S S, Chandra S T, Leslie M C. Developing a flexible SPEAR3-based psychophysical research platform for testing cochlear implant users. Durham, NC: Duke University, 2008.
5. Fatemeh S, Taher M, Nasser K. A multi-band environment-adaptive approach to noise suppression for cochlear implant//36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Chicago, 2014: 1699-1702.
6. Mirzahasanloo T, Gopalakrishna V, Kehtarnavaz N, et al. Adding real-time noise suppression capability to the cochlear implant PDA research platform//34th Annual International Conference of the IEEE EMBS, San Diego, 2012: 2271-2274.
7. Mirzahasanloo T S, Kehtarnavaz N, Panahi I. Adding quiet and music detection capabilities to FDA-approved cochlear implant research platform//8th International Symposium on Image and Signal Processing and Analysis, Trieste, 2013: 399-403.
8. 陈又圣, 宫琴. 基于双 TP 型麦克风的电子耳蜗前端指向性语音增强系统的研制. 仪器仪表学报, 2010, 31(9): 1952-19580.
9. Chen Yousheng, Gong Qin. Broadband beamforming compensation algorithm in CI front-end acquisition, Biomed Eng Online, 2013: 18.
10. Chen Yousheng, Gong Qin. Head influence platform for cochlear implant//World Congress on Medical Physics and Biomedical Engineering, Beijing, 2013, 39: 1468-1471.
11. Skinner M W, Holder L K, Whitford L A. Speech recognition with the nucleus 24 SPEAK, ACE, and CIS speech coding strategies in newly implanted adults. Ear Hear, 2002, 23(3): 207-223.
12. Psarros C E, Plant K L, Lee K, et al. Conversion from the SPEAK to the ACE strategy in children using the Nucleus 24 cochlear implant system: Speech perception and speech production outcomes. Ear Hear, 2002, 23(1, S): 18S-27S.
13. Ziese M, Stutzel A, von Specht H. Speech understanding with the CIS and the n-of-m strategy in the MED-EL COMBI 40+ system. Orl-J Oto-Rhino-Laryngol, 2000, 62(6): 321-329.
14. Buechner A, Frohne C, Boyle P. A high rate n-of-m speech processing strategy for the first generation Clarion cochlear implant. Int J Audiol, 2009, 48(12): 868-875.

Journal of Biomedical Engineering

Research on spectrum feature of speech processing strategy for cochlear implant

Abstract Full text Figures/Tables Video References Cited by

Previous Article

Next Article

Format

Content