• Journal of Korea Society of Digital Industry and Information Management
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• v.12 no.1
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• pp.43-50
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• 2016

This paper is on an acoustic echo canceller solving the double-talk problem by using the blind signal separation technology. The acoustic echo canceller may be deteriorated or diverged during the double-talk period. So we use the blind signal separation to detect the double talking by separating the near-end speech signal from the mixed microphone signal. The blind signal separation extracts the near-end signal from dual microphones by the iterative computations using the 2nd order statistical character in the closed reverberation environment. By this method, the acoustic echo canceller operates irrespective of the double-talking. We verified performances of the proposed acoustic echo canceller in the computer simulations. The results show that the acoustic echo canceller with this algorithm detects the double-talk periods well, and then operates stably without diverging of the coefficients after ending the double-talking. The merits are in the simplicity and stability.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.5C
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• pp.478-486
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• 2007

Double-talk detection errors can result in either large residual echo or distorting the near-end talker's input speech. Thus accurate double-talk detection is an important problem in the acoustic echo canceller to improve the speech quality. In the double-talk detection algorithm using a cross-correlation coefficient, double-talk detection errors can occur in the initial convergence period of an adaptive filter or in noisy environment since the cross-correlation coefficient becomes large in such situations. In this paper, we propose a new double-talk detection algorithm based on the cross-correlation method using a normalized error signal power to reduce the double-talk detection errors. The experimental results have shown the performance improvement of an acoustic echo canceller as well as the noise-robustness of the proposed double-talk detector.

• The Journal of the Acoustical Society of Korea
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• v.19 no.7
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• pp.34-41
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• 2000

This paper proposes a new double-talk detection algorithm which is based on the fuzzy rules, in the adaptive echo canceller of telecommunication system. In this method, the two inputs of the fuzzy inference for detecting double-talk condition are used. One is the cross-correlation coefficient between the error signal and the primary signal which is the summation of the real echo signal and the near-end signal. The other one is the cross-correlation coefficient between the estimation error signal and the primary signal. The fuzzy controller makes a fuzzification for two inputs by the membership functions of trapezoid does the max-min composition using if-then rules. The composed result is defuzzificated by the center gravity method. And by defuzzificated values, the double-talt the echo path variance, and the echo path variance during the double-talk are detected. It is confirmed by computer simulation that this fuzzy double-talk detector is able to estimate the double talk and the echo path variation condition, and even track echo path variation more accurately than the conventional algorithm during the double-talk period.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2362-2367
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• 2005

This paper reports a technique for discriminating double talk and echo path change using the stochastic characteristics of power change for an adaptive noise canceller. The causes of rapid error increasing are double talk and echo path change. When the echo path is changed, the system corrects the impulse response in order to reduce the error. However, in the case of double talk, the system has to suspend the updating impulse response in order to maintain the quality of the voice signal. In the conventional system, it was difficult to discriminate between the two situations. In this research, the stochastic characteristics of the voice power change in the double talk period were experimentally verified to be different from the power change during echo path changing. Based on the results, a new double talk detection method is proposed.

• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.2302-2304
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• 2001

In the double-talk situation where both the near-end and far-end signal present, the performance of echo cancellation using the conventional LMS algorithm is degraded easily since it freezes the adaptation in this situation. Recently CLMS and ECLMS algorithm were proposed to solve this problem. These algorithms could be used to adapt the filter's parameters continuously even in the double-talk situation. In this paper, we compare and analyze their performance. The computer simulation was performed and the results showed as that both algorithms were robust and kept the desirable performance even in the double-talk situation.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.10a
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• pp.471-473
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• 2009

In this paper, we propose a double talk and noise robust acoustic echo canceler for hands-free telephony applications. The proposed system includes a double-talk detection method that detects the double-talk durations, which uses covariance between microphone input signa and estimated microphone input signal. And proposed adaptive algorithm for estimating acoustic echo path, uses normalized auto-covariance matrix of input signal with multiplication of residual error power and projection order of AP(affine projeciton) algorithm. It is confirmed that the proposed algorithm shows better performance from acoustic interference cancellation (AIC) viewpoint in double talk and noisy environments.

• The Journal of the Acoustical Society of Korea
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• v.28 no.4
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• pp.401-407
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• 2009

In this paper, we propose a novel method for the cross-correlation based double-talk detection (DTD), which employing the Gaussian Mixture Model (GMM) in the frequency domain. The proposed algorithm transforms the cross correlation coefficient used in the time domain into 16 channels in the frequency domain using the discrete fourier transform (DFT). The channels are then selected into seven feature vectors for GMM and we identify three different regions such as far-end, double-talk and near-end speech using the likelihood comparison based on those feature vectors. The presented DTD algorithm detects efficiently the double-talk regions without Voice Activity Detector which has been used in conventional cross correlation based double-talk detection. The performance of the proposed algorithm is evaluated under various conditions and yields better results compared with the conventional schemes. especially, show the robustness against detection errors resulting from the background noises or echo path change which one of the key issues in practical DTD.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.6
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• pp.628-633
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• 2014

This paper proposes a performance improvement method of the conventional double talk detection method which can operate before convergence of the echo canceller. The proposed method estimates the coefficients of the linear predictive coding(LPC) filter by using the primary input signal. The time-varying threshold for double talk detection is determined based on the LPC filter gain of the primary input signal level. The proposed method can reduce not only false detection rate which means wrong detection of single talk as double talk but also double talk detection delay. Computer simulation was performed using a long-term real speech signals. It is shown that the proposed method improves the conventional method in terms of lowering the false detection rate and shortening the detection delay.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.4C
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• pp.343-349
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• 2010

In this paper, we study real time AEC (acoustic echo canceller) based on NLMS adaptive filter. Proposed method improves conversation quality by enhancing the performance of AEC during double talk section and reduces the power consumption by controling the adaption operation of NLMS adaptive filter. Proposed method examines the convergence of the NLMS adaptive filter, stores the estimated echo path and chooses operation of NLMS adaptive filter. Furthermore if double talk is detected, the proposed AEC utilizes the stored echo path optionally considering missed double talk time. When the proposed AEC is used, the performance of the AEC is enhanced although the simple double talk detector is used and the power consumption of the AEC is reduced.

• Proceedings of the KIEE Conference
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• 2001.11c
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• pp.142-145
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• 2001

In the double-talk situation where both the near-end and far-end signal present, the performance of echo cancellation using the NLMS algorithm is degraded easily since it freezes the adaptation in this situation. To solve this problem, which utilize the correlation function values of input signal instead of the input signal itself, have been proposed. Because this algorithm could be used to adapt the filter's parameters continuously even in the double-talk situation, give good convergence property compared with the NLMS. In this paper, we compare and analyze its performance. The computer simulation was performed and the results showed as that ECLMS algorithms were robust and kept the desirable performance even in the double-talk situation.