인공와우 어음처리방식을 위한 적응효과 알고리즘의 음성개시점 검출 특성 비교
Comparison of Speech Onset Detection Characteristics of Adaptation Algorithms for Cochlear Implant Speech Processor
2
조회
0
다운로드
0
인용
0
참고문헌
키워드
초록
It is well known that temporal information, i.e. speech onset, about input speech can be represented to the response nerve signal of auditory nerve better depending on the adaptation effect occurred in the auditory nerve synapse. In addition, the performance of a speech processor of cochlear implant can be improved by the adaptation effect. In this paper, we observed the emphasis characteristic of speech onset in the recently proposed adaptation algorithm, analyzed the characteristic of performance change according to the variation of parameters and compared with transient emphasis spectral maxima (TESM) is the previous typical strategy. When observing false peaks which are generated everywhere except speech onset, in the case of the proposed model, the false peak were generated much less than in the case of the TESM and it is more distinguishable under noise.
Abstract
It is well known that temporal information, i.e. speech onset, about input speech can be represented to the response nerve signal of auditory nerve better depending on the adaptation effect occurred in the auditory nerve synapse. In addition, the performance of a speech processor of cochlear implant can be improved by the adaptation effect. In this paper, we observed the emphasis characteristic of speech onset in the recently proposed adaptation algorithm, analyzed the characteristic of performance change according to the variation of parameters and compared with transient emphasis spectral maxima (TESM) is the previous typical strategy. When observing false peaks which are generated everywhere except speech onset, in the case of the proposed model, the false peak were generated much less than in the case of the TESM and it is more distinguishable under noise.
참고문헌 (13)
- B. S. Wilson, "Better speech recognition with cochlear implants", Nature, 352(6332), pp.236~238 (1991)
- 김두희, "Neural Spike Train Decoding에 기반한 인공와우 어음처리방식 성능평가", 의공학회지, 28(2), pp.271~279 (2007), 대한의용생체공학회
- B. S. Wilson, "Two new directions in speech processor design for cochlear implants", Ear Hear, 26(4), pp.73S~81S (2005)
- J. Tchorz, "A model of auditory perception as front end for automatic speech recognition", J. Acoust. Soc. Am, 106(4), pp.2040~2050 (1999)
- A. E. Vandali, "Emphasis of short-duration acoustic speech cues for cochlear implant users", J. Acoust. Soc. Am, 109(5), pp.2049~2061 (2001)
- J. H. Kim, K. H. Kim, "A novel speech processing strategy for cochlear implants based on nonlinear model of auditory periphery", proc. 34th KOSOMBE, pp.152~155 (2006)
- 김진호, "청각신경 시냅스의 적응 효과를 이용한 인공와우 어음처리 알고리즘의 개선에 대한 시뮬레이션 연구", 의공학회지, 28(2), pp.205~211 (2007), 대한의용생체공학회
- L. A. Westerman, "Rapid and short-term adaptation in auditory nerve responses", Hear. Res, 15(3), pp.249~260 (1984)
- P. C. Loizou, "On the number of channels needed to understand speech", J. Acoust. Soc. Am, 106(4), pp.2097~2103 (1999)
- X. Zhang, "Analysis of models for the synapse between the inner hair cell and the auditory nerve", J. Acoust. Soc. Am, 118(3), pp.1540~1553 (2005)
- G.. S. Donaldson, "Effects of vowel context on the recognition of initial and medial consonants by cochlear implant users", Ear Hear, 27(6), pp.658~677 (2006)
- E. Kennedy, "Consonant- vowel intensityratios for maximizing consonant recognition by hearing-impaired listeners", J. Acoust. Soc. Am, 103(2), pp.1098~1114 (1998)
- L. Yang, "Spectral subtraction-based speech enhancement for cochlear implant patients in background noise", J. Acoust. Soc. Am, 117(3), pp.1001~1004 (2005)