Abstract
The properties of noise signals can be the main problem associated with noise cancellation systems. In order to overcome this problem, high complexity algorithms have to be used in order to reduce the noise embedded in the useful signals such as speech. This method can be impractical, especially in real-time applications where the computational power is a crucial issue. Adaptive filters give applicable solutions, but most literature proposed a single, yet complex algorithm to removing the noise. This paper proposes an alternative approach to eliminate background noise in corrupted speech signals. The method is achieved by letting the system assigns an appropriate algorithm according to the characteristics of the noise. The criterion used here is based on the calculation of eigenvalue spread in the autocorrelation matrix of the input signal. In addition, an algorithm derived from set-membership filtering is also used among the selected algorithms. This approach showed its potential capability in eliminating different types of environmental noise from corrupted speech signals. The technique presented here exhibited fast convergence speed and improvement in signal-to-noise ratio compared with other single adaptive algorithms.
| Original language | English |
|---|---|
| Title of host publication | 2014 IEEE Student Conference on Research and Development, SCOReD 2014 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| ISBN (Electronic) | 9781479964284 |
| DOIs | |
| Publication status | Published - 30 Mar 2014 |
| Event | 2014 IEEE Student Conference on Research and Development, SCOReD 2014 - Penang, Malaysia Duration: 16 Dec 2014 → 17 Dec 2014 |
Other
| Other | 2014 IEEE Student Conference on Research and Development, SCOReD 2014 |
|---|---|
| Country | Malaysia |
| City | Penang |
| Period | 16/12/14 → 17/12/14 |
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Keywords
- adaptive algorithm
- adaptive filtering
- eigenvalue spread
- environmental noise
- noise cancellation
ASJC Scopus subject areas
- Computer Science(all)
- Electrical and Electronic Engineering
- Energy(all)
Cite this
A selective algorithm for the reduction of irregular noise in speech communication. / Ramli, Roshahliza M.; Abdul Samad, Salina; Abid Noor, Ali O.
2014 IEEE Student Conference on Research and Development, SCOReD 2014. Institute of Electrical and Electronics Engineers Inc., 2014. 7072962.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - A selective algorithm for the reduction of irregular noise in speech communication
AU - Ramli, Roshahliza M.
AU - Abdul Samad, Salina
AU - Abid Noor, Ali O.
PY - 2014/3/30
Y1 - 2014/3/30
N2 - The properties of noise signals can be the main problem associated with noise cancellation systems. In order to overcome this problem, high complexity algorithms have to be used in order to reduce the noise embedded in the useful signals such as speech. This method can be impractical, especially in real-time applications where the computational power is a crucial issue. Adaptive filters give applicable solutions, but most literature proposed a single, yet complex algorithm to removing the noise. This paper proposes an alternative approach to eliminate background noise in corrupted speech signals. The method is achieved by letting the system assigns an appropriate algorithm according to the characteristics of the noise. The criterion used here is based on the calculation of eigenvalue spread in the autocorrelation matrix of the input signal. In addition, an algorithm derived from set-membership filtering is also used among the selected algorithms. This approach showed its potential capability in eliminating different types of environmental noise from corrupted speech signals. The technique presented here exhibited fast convergence speed and improvement in signal-to-noise ratio compared with other single adaptive algorithms.
AB - The properties of noise signals can be the main problem associated with noise cancellation systems. In order to overcome this problem, high complexity algorithms have to be used in order to reduce the noise embedded in the useful signals such as speech. This method can be impractical, especially in real-time applications where the computational power is a crucial issue. Adaptive filters give applicable solutions, but most literature proposed a single, yet complex algorithm to removing the noise. This paper proposes an alternative approach to eliminate background noise in corrupted speech signals. The method is achieved by letting the system assigns an appropriate algorithm according to the characteristics of the noise. The criterion used here is based on the calculation of eigenvalue spread in the autocorrelation matrix of the input signal. In addition, an algorithm derived from set-membership filtering is also used among the selected algorithms. This approach showed its potential capability in eliminating different types of environmental noise from corrupted speech signals. The technique presented here exhibited fast convergence speed and improvement in signal-to-noise ratio compared with other single adaptive algorithms.
KW - adaptive algorithm
KW - adaptive filtering
KW - eigenvalue spread
KW - environmental noise
KW - noise cancellation
UR - http://www.scopus.com/inward/record.url?scp=84983190511&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84983190511&partnerID=8YFLogxK
U2 - 10.1109/SCORED.2014.7072962
DO - 10.1109/SCORED.2014.7072962
M3 - Conference contribution
BT - 2014 IEEE Student Conference on Research and Development, SCOReD 2014
PB - Institute of Electrical and Electronics Engineers Inc.
ER -