지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- 대한전자공학회 IEIE Transactions on Smart Processing & Computing IEIE Transactions on Smart Processing & Computing Vol.13 No.2
- 발행연도
- 2024.4
- 수록면
- 176 - 185 (10page)
- DOI
- 10.5573/IEIESPC.2024.13.2.176
이용수
초록· 키워드
오류제보하기
Broadband speech encoding and decoding methods are important for achieving highquality speech communication and audio applications. However, encoding and decoding algorithms often face problems such as large data-transmission volume and high computational complexity. To overcome these problems, a wideband speech codec algorithm is proposed based on compressed sensing and fractional calculus. Compressed sensing theory was used to sparsely represent wideband speech signals. The concept and method of fractional calculus are introduced to analyze and process wideband speech signals. Algebraic codebooks were used to adapt the structure and bit allocation of speech based on its different states and actual encoding and decoding rates. Embedded encoding and decoding of wideband speech can be achieved by adding and generating digital book pulses layer by layer. The results show that the proposed algorithm has a minimum encoding and decoding rate of 6.9 bits/s and a speech quality score of over 4.0. It also has low latency and high speed for speech encoding and decoding and provides high-quality speech evaluation. It has clear advantages in speech quality and data transmission efficiency. This study could provide new ideas and methods for further research and application of broadband speech coding and decoding.
목차
Abstract
1. Introduction
2. Broadband Voice Processing
3. Wideband Speech Coding and Decoding Algorithm
4. Experiment with Speech Encoder based on Calculus
5. Conclusion
References
참고문헌 (20)
참고문헌 신청
V. Parthasaradi, P.Kailasapathi, “A novel MFCC-NN learning model for voice communication through Li-Fi for motion control of a robotic vehicle,” Soft Computing, 2019, vol. 23, no. 18, pp. 8651-8660. Article (CrossRef Link)
K. A. Berg, J. H. Noble, B. Dawant, R. Dwyer, R. Labadie, R. H. Gifford, “Effect of number of channels and speech coding strategy on speech recognition in mid-scala electrode recipients,” The Journal of the Acoustical Society of America, 2019, vol. 145, no. 3, pp. 1796-1797. Article (CrossRef Link)
T. Bentsen, S. J. Mauger, A. A. Kressner, T. May, T. Dau, “The impact of noise power estimation on speech intelligibility in cochlear-implant speech coding strategies,” The Journal of the Acoustical Society of America, 2019, vol. 145, no. 2, pp. 818-821. Article (CrossRef Link)
S. Parida, M. G. Heinz, “Effects of noise-induced hearing loss on speech-in-noise envelope coding: Inferences from single-unit and non-invasive measures in animals,” The Journal of the Acoustical Society of America, 2019, vol. 145, no. 3, pp. 1716-1716. Article (CrossRef Link)
C. Yang, Y. F. Liu, X. X. Xu, H. Zhu, C. H. Liu, “Speech signal encoding algorithm based on predictive coding and vector coding” Modern Electronics Technique, 2018, vol. 41, no. 24, pp. 128-131.
K. A. Berg, J. H. Noble, B. Dawant, R. Dwyer, R. Labadie, R. H. Gifford, “Effect of number of channels and speech coding strategy on speech recognition in mid-scala electrode recipients,” The Journal of the Acoustical Society of America, 2019, vol. 145, no. 3, pp. 1796-1797. Article (CrossRef Link)
T. Bentsen, S. J. Mauger, A. A. Kressner, T. May, T. Dau, “The impact of noise power estimation on speech intelligibility in cochlear-implant speech coding strategies,” The Journal of the Acoustical Society of America, 2019, vol. 145, no. 2, pp. 818-821. Article (CrossRef Link)
S. Parida, M. G. Heinz, “Effects of noise-induced hearing loss on speech-in-noise envelope coding: Inferences from single-unit and non-invasive measures in animals,” The Journal of the Acoustical Society of America, 2019, vol. 145, no. 3, pp. 1716-1716. Article (CrossRef Link)
C. Yang, Y. F. Liu, X. X. Xu, H. Zhu, C. H. Liu, “Speech signal encoding algorithm based on predictive coding and vector coding” Modern Electronics Technique, 2018, vol. 41, no. 24, pp. 128-131.
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