• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.12
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• pp.1337-1344
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• 2014

The objective of an echo canceller connected to any end of a communication line such as digital subscriber line (DSL) is to compensate the outgoing transmit signal in the receiving path that the hybrid circuit leaks. The echo canceller working in a full duplex environment is an adaptive system driven by the local signal. Conventional echo canceller that implement the least mean square (LMS) algorithm provides a low computational burden but poor convergence properties. The length of the echo canceller will directly affect both the degree of performance and the convergence speed of the adaptation process. To cancel long time-varying echoes, the number of tap coefficients of a conventional echo canceller must be large, which decreases the convergence speed of the adaptive filter. This paper proposes an alternative technique for the echo cancellation in a telecommunication channel. The new technique employs the bi-directional least mean square (LMS) algorithm for adaptively computing the optimal set of the coefficients of the echo canceller, which is composed of weighted combination of both feedforward and feedback algorithms. Finally, Simulation results as well as mathematical analysis demonstrates that the proposed echo canceller has faster convergence speed than the conventional LMS echo canceller with nearly equivalent complexity of computation.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.6
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• pp.1249-1256
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• 2019

In this paper, we propose a new algorithm to remove acoustic feedback and noise in hearing aids. Instead of using the conventional FIR structure, this algorithm is a deep learning algorithm using neural network adaptive prediction filter to improve the feedback and noise reduction performance. The feedback canceller first removes the feedback signal from the microphone signal and then removes the noise using the Wiener filter technique. Noise elimination is to estimate the speech from the speech signal containing noise using the linear prediction model according to the periodicity of the speech signal. In order to ensure stable convergence of two adaptive systems in a loop, coefficient updates of the feedback canceller and noise canceller are separated and converged using the residual error signal generated after the cancellation. In order to verify the performance of the feedback and noise canceller proposed in this study, a simulation program was written and simulated. Experimental results show that the proposed deep learning algorithm improves the signal to feedback ratio(: SFR) of about 10 dB in the feedback canceller and the signal to noise ratio enhancement(: SNRE) of about 3 dB in the noise canceller than the conventional FIR structure.

• Speech Sciences
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• v.11 no.4
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• pp.89-97
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• 2004

In this paper, an improved network echo canceller is proposed. The proposed echo canceller is based on the LTJ(lattice transversal joint) adaptive filter which uses informations from the speech decoder. In the proposed implementation method of the network echo canceller, the filer coefficients of the transversal filter part in the LTJ adaptive filter is updated every other sample instead of every sample. So its complexity can be lower than that of the transversal filter. And the echo cancellation rate can be improved by residual echo cancellation using the lattice predictor whose order is less than 10. Computational complexity of the proposed echo canceller is lower than that of the transversal filter but the convergence speed is faster than that of the transversal filter. The performance improvement of the proposed echo canceller was verified by the experiments using the real speech signal and speech coder.

• Speech Sciences
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• v.8 no.2
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• pp.73-81
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• 2001

In this paper, we focus on the real time implementation of the single channel adaptive noise canceller(ANC) by using TMS320C30 EVM board. The implemented single channel adaptive noise canceller is based on a reference paper [1] in which it is simulated by using the recursive average magnitude difference function(AMDF) to get a properly delayed input speech on a sample basis as a reference signal and normalized least mean square(NLMS) algorithm. To certify results of the real time implementation, we measured the processing time of the ANC and enhancement ratio according to various signalto-noise ratios(SNRs). Experimental results demonstrate that the processing time of the speech signal of 32ms length with delay estimation of every 10 samples is about 26.3 ms, and almost the same performance as given in [1] is obtained with the implemented system.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.30 no.1
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• pp.88-94
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• 2019

A leakage canceller and adaptive algorithm for FMCW Radar is presented. Because a strong leakage signal causes various problems in the transceiver and digital processor, specific FMCW radars are in need of a leakage canceller. The leakage canceller has an adaptive structure and the algorithm calculates the prediction vector and learns the adaptive coefficient simultaneously. The proposed algorithm an improvement of 10 dB in the cancellation performance.

• Journal of Korea Multimedia Society
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• v.10 no.8
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• pp.1004-1016
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• 2007

In this paper we proposed a Weight-Update-Control Adaptive Noise Canceller which improves speech when environmental noise is stationary and it is hard to acquire a reference signal. Adaptive Noise Canceller(ANC) needs a reference signal, but it is not easy to measure pure noise without voice for reference in factory. Because there are mixed various mechanical noise and workers' voice. Therefore ANC is not suitable to reduce background noise. So we proposed the method that uses an arbitrary constant as an input signal and inputs microphone signal to the reference signal. The noise is eliminated using updated weights in non-speech range. In speech range the weight is fixed and the modified voice is acquired then voice is restored through transversal filter. The proposed method is based on facts that the factory noise is stationary and the noise is not changed in short conversation range. As a result of simulation using MATLAB, we confirmed that the proposed method is effective for reducing factory noise and has high signal to noise ratio(SNR).

• ETRI Journal
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• v.38 no.2
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• pp.366-375
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• 2016

This paper describes an algorithm to suppress composite noise in a two-microphone speech enhancement system for robust hands-free speech communication. The proposed algorithm has four stages. The first stage estimates the power spectral density of the residual stationary noise, which is based on the detection of nonstationary signal-dominant time-frequency bins (TFBs) at the generalized sidelobe canceller output. Second, speech-dominant TFBs are identified among the previously detected nonstationary signal-dominant TFBs, and power spectral densities of speech and residual nonstationary noise are estimated. In the final stage, the bin-wise output signal-to-noise ratio is obtained with these power estimates and a Wiener post-filter is constructed to attenuate the residual noise. Compared to the conventional beamforming and post-filter algorithms, the proposed speech enhancement algorithm shows significant performance improvement in terms of perceptual evaluation of speech quality.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.16 no.12
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• pp.1219-1228
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• 1991

In the actual case, a model of noise canceller using adaptive filter has both a channel transfer function from noise source to main signal input and to noise canceller input. The previous models of noise canceller have been considered to be only one side channel transfer function. Therefore, it is proposed that a new model has two channel transfer functions and derives an optimal tranfer function of adaptive noise canceller. The adaptive filter is using the joint process lattice filter that has fast adaptive speed. The signal noise radio has been improved by a model of ANC-ALE and it is confirmed with computer simulation. Beside, a dc bias is very effective for noise cancelling, especially to the particular signal.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.8
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• pp.2033-2042
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• 1996

In this papre, we describe a recently implemented echo canceller for digital cellular communication of Code Division Multiple Access(CDMA) that features time sharing of digital signal processor(DSP) over four channels in one DSP to reduce per channel costs. In the Public Land Mobile Network(PLMN), it is important to cancel the echo reflected from the Public Switched Telephone Network(PSTN) side. In case of digital mobile system, the round-trip delay of the echo is in excess of about 180 milliseconds due to frame-by-frame voice coding. It is necessary to cancel the echo in PLMN. We have developed a multi-channel echo canceller tht operates with Time Switch Module in a Mobile Switching Center(MSC). The general echo canceller needs PCM trunk interface circuits and the tone detection and disabling circuits, but the multi-channel echo canceller linked with Time Switch Module does not need them. Therefore we could develop the effective and economical echo canceller.

• Speech Sciences
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• v.13 no.1
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• pp.117-128
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• 2006

The two-channel Generalized Sidelobe Canceller (GSC) scheme suffers from the presence of leakage signal in the reference channel. The leakage signal is caused by the dissimilar impulse responses between microphones, and different paths from speech source to microphones. Such leakage is detrimental to speech enhancement of the GSC since the desired reference signal becomes corrupted. In order to suppress the signal leakage, two matrix injection methods are proposed. In the first method, a simple gain compensation matrix is used. In the second, a projection matrix for reducing the error between the actual and the ideal primary and reference signals, is used. This paper describes the performance degradation resulting from leakage, and proposes effective methods to resolve the problem. Representative experiments were conducted to demonstrate the effectiveness of the proposed methods on recorded speech and noise in an actual automobile environment.