Abstract
Some of the teething problems associated in the use of two-sensor noise cancellation systems are the nature of the noise signals—a problem that imposes the use of highly complex algorithms in reducing the noise. The usage of such methods can be impractical for many real time applications, where speed of convergence and processing time are critical. At the same time, the existing approaches are based on using a single, often complex adaptive filter to minimize noise, which has been determined to be inadequate and ineffective. In this paper, a new mechanism is proposed to reduce background noise from speech communications. The procedure is based on a two-sensor adaptive noise canceller that is capable of assigning an appropriate filter adapting to properties of the noise. The criterion to achieve this is based on measuring the eigenvalue spread based on the autocorrelation of the input noise. The proposed noise canceller (INC) applies an adaptive algorithm according to the characteristics of the input signal. Various experiments based on this technique using real-world signals are conducted to gauge the effectiveness of the approach. Initial results illustrated the system capabilities in executing noise cancellation under different types of environmental noise. The results based on the INC technique indicate fast convergence rates; improvements up to 30 dB in signal-to-noise ratio and at the same time shows 65% reduction of computational power compared to conventional method.
| Original language | English |
|---|---|
| Pages (from-to) | 1-8 |
| Number of pages | 8 |
| Journal | International Journal of Speech Technology |
| DOIs | |
| Publication status | Accepted/In press - 3 Jun 2017 |
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Keywords
- Adaptive algorithms
- Adaptive filtering
- Eigenvalue spread
- Environmental noise
- Noise cancellation
ASJC Scopus subject areas
- Software
- Language and Linguistics
- Human-Computer Interaction
- Linguistics and Language
- Computer Vision and Pattern Recognition
Cite this
Noise cancellation using selectable adaptive algorithm for speech in variable noise environment. / Ramli, Roshahliza M.; Noor, Ali O.Abid; Abdul Samad, Salina.
In: International Journal of Speech Technology, 03.06.2017, p. 1-8.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Noise cancellation using selectable adaptive algorithm for speech in variable noise environment
AU - Ramli, Roshahliza M.
AU - Noor, Ali O.Abid
AU - Abdul Samad, Salina
PY - 2017/6/3
Y1 - 2017/6/3
N2 - Some of the teething problems associated in the use of two-sensor noise cancellation systems are the nature of the noise signals—a problem that imposes the use of highly complex algorithms in reducing the noise. The usage of such methods can be impractical for many real time applications, where speed of convergence and processing time are critical. At the same time, the existing approaches are based on using a single, often complex adaptive filter to minimize noise, which has been determined to be inadequate and ineffective. In this paper, a new mechanism is proposed to reduce background noise from speech communications. The procedure is based on a two-sensor adaptive noise canceller that is capable of assigning an appropriate filter adapting to properties of the noise. The criterion to achieve this is based on measuring the eigenvalue spread based on the autocorrelation of the input noise. The proposed noise canceller (INC) applies an adaptive algorithm according to the characteristics of the input signal. Various experiments based on this technique using real-world signals are conducted to gauge the effectiveness of the approach. Initial results illustrated the system capabilities in executing noise cancellation under different types of environmental noise. The results based on the INC technique indicate fast convergence rates; improvements up to 30 dB in signal-to-noise ratio and at the same time shows 65% reduction of computational power compared to conventional method.
AB - Some of the teething problems associated in the use of two-sensor noise cancellation systems are the nature of the noise signals—a problem that imposes the use of highly complex algorithms in reducing the noise. The usage of such methods can be impractical for many real time applications, where speed of convergence and processing time are critical. At the same time, the existing approaches are based on using a single, often complex adaptive filter to minimize noise, which has been determined to be inadequate and ineffective. In this paper, a new mechanism is proposed to reduce background noise from speech communications. The procedure is based on a two-sensor adaptive noise canceller that is capable of assigning an appropriate filter adapting to properties of the noise. The criterion to achieve this is based on measuring the eigenvalue spread based on the autocorrelation of the input noise. The proposed noise canceller (INC) applies an adaptive algorithm according to the characteristics of the input signal. Various experiments based on this technique using real-world signals are conducted to gauge the effectiveness of the approach. Initial results illustrated the system capabilities in executing noise cancellation under different types of environmental noise. The results based on the INC technique indicate fast convergence rates; improvements up to 30 dB in signal-to-noise ratio and at the same time shows 65% reduction of computational power compared to conventional method.
KW - Adaptive algorithms
KW - Adaptive filtering
KW - Eigenvalue spread
KW - Environmental noise
KW - Noise cancellation
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U2 - 10.1007/s10772-017-9425-1
DO - 10.1007/s10772-017-9425-1
M3 - Article
SP - 1
EP - 8
JO - International Journal of Speech Technology
JF - International Journal of Speech Technology
SN - 1381-2416
ER -