• 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.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.5
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• pp.979-986
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• 2018

This paper deals with acoustic echo cancellation using blind signal separation method. This method does not degrade the echo cancellation performance even during double-talk. In the closed echo environment, the mixing model of acoustic signals is multi-channel, so the convolutive blind signal separation method is applied and the mixing coefficients are calculated by using the feedback model without directly calculating the separation coefficients for signal separation. The coefficient update is performed by iterative calculations based on the second-order statistical properties, thus estimates the near-end speech. A number of simulations have been performed to verify the performance of the proposed blind signal separation method. The simulation results show that the acoustic echo canceller using this method operates safely regardless of the presence of double-talk, and the PESQ is improved by 0.6 point compared with the general adaptive FIR filter structure.

• The Journal of the Acoustical Society of Korea
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• v.28 no.5
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• pp.483-490
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• 2009

In this paper, we develop a speech interface that has acoustic echo cancelling and barge-in functionalities in the car environment. In the echo canceller, DT (Double-Talk) detection algorithm using the correlation coefficients between reference and desired signals can make DT detection errors often in the background noise. We reduce the DT detection errors by using the average power of noise and echo estimated from the input signal. In addition, to make it possible for drivers to give speech command to the system by interrupting the speaker output, barge-in functionality is implemented with the combination of DT detection and appropriate gain control of the speaker output. Through the computer simulation with the assumed car environment and experiment in the real laboratory environment, implemented speech interface has shown good performance in removing acoustic echo signals in the noisy environment with proper operation of barge-in functionality.

• The Journal of the Acoustical Society of Korea
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• v.28 no.7
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• pp.680-685
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• 2009

In this paper, we propose a efficient noise power estimation technique for an integrated acoustic echo and noise suppression system in a frequency domain. The proposed method uses speech absence probability (SAP) derived from the microphone input signal as the smoothing parameter updating noise power to reduce the noise power estimation error resulted from the distortions in the unified structure where the noise suppression (NS) operation is placed after the acoustic echo suppression (AES) algorithm. Therefore, in the proposed approach, the smoothing parameter based on SAP derived from the input signal instead of echo-suppressed signal should stop updating noise power estimates during the distorted noise spectrum periods. The performance of the proposed algorithm is evaluated by the objective test under various environments and yields better results compared with the conventional scheme.

• Proceedings of the Korea Multimedia Society Conference
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• 2000.04a
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• pp.141-144
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• 2000

스테레오 음향 반향 제거기는 채널신호간에 상호상관(cross-correlation) 때문에 적응필터 계수가 수신실의 반향 경로를 정확하게 추정하지 못한다. 본 논문에서는 상호상관을 줄이기 위해서 채널신호간 차의 절대값과 시변 감쇠상수를 이용하는 새로운 전처리 필터를 제안한다. 시뮬레이션을 통해서 제안하는 전처리 필터가 기존의 방법에 비해서 우수함을 보인다.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.5
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• pp.538-542
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• 2018

Echo generated in digital hearing aid vent give rise to user's discomfort. For cancelling feedback echo in vent, it is required to estimate vent impulse response exactly. The vent impulse response has time varying and sparse characteristics. The IPNLMS has been known a useful adaptive algorithm to estimate vent impulse response with these characteristics. In this paper, subband sparse adaptive filter which applying IPNLMS to subband hearing aid structure is proposed to cancel echo of vent by estimating sparse vent impulse response. In the propose method, the decomposition of input signal to subband can pre-whiten each subband signal, so adaptive filter convergence speed can be improved. And the poly phase component decomposition of adaptive filter increases sparsity of each components, and the better echo cancellation can be possible without additional computation. To derive coefficients update equation of the adaptive filter, by defining the cost function based weight NLMS is defined, and the coefficient update equation of each subband is derived. For verifying performances of the adaptive filter, convergence speed, and steady state error by white signal input, and echo cancelling results by real speech input are evaluated by comparing conventional adaptive filters.

• The Journal of the Acoustical Society of Korea
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• v.28 no.5
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• pp.454-460
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• 2009

In this paper, we propose a residual echo and noise reduction scheme by using linear predictor for hands-free telephony applications. The proposed scheme whitens residual echo by the linear prediction during the non double-talk. But whitened residual echo signal still has speech characteristics. In this scheme, the whitened residual echo signal is more whitened by using the power of the linear prediction error signal and the linear predicted signal. After whitening process, near-end speech and ambient noise is present during double-talk but white noise will appear during non double-talk situation. By linearly predicting again the combined signal of the near-end speech and the whitened signal, the ambient noise is removed. Through computer simulation, it is shown that the proposed method performs well at the side of AIC (acoustic interference cancellation).

• The Journal of the Acoustical Society of Korea
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• v.18 no.5
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• pp.3-11
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• 1999

The conventional stereophonic acoustic echo cancellers need two adaptive filters to estimate one channel echo signal. Since the two channel signals are strongly correlated, the ESR of the input signals is considerably increased whatever the input signals may be. This causes the slow convergence of the adaptive filter for echo cancellation. To speed up the convergence, the AP algorithm is frequently used for the stereophonic acoustic echo canceller although there isn't a fast version for 2-channel case. The AP algorithm can be approximated with the Gram-Schmidt orthogonalization and a TDL structure. We propose a two channel algorithm for stereophonic acoustic echo canceller with the approximated AP algorithm.

• Journal of Korea Multimedia Society
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• v.3 no.4
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• pp.347-355
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• 2000

This paper presents an adaptive AEC(acoustic echo canceller) based on the wavelet transform using M-channel subband QMF filter banks. The proposed algorithm improves the performance of AEC with a realtime process by a low complexity of wavelet transform filter banks, a subband processing and a orthogonality of wavelet subband filter. Adaptive filter coefficients of each subband are updated using LMS algorithm with a low complexity and a easy realization for a realtime processing and a reduction of hardware cost. For a input signal, a white Gaussian noise and a real speech signal with a environment noises are used for a performance estimation of the proposed algorithm. As a result of computer simulation, the proposed AEC has a low asymptotic error, a low computation complexity and a robust performance.

• Journal of Digital Convergence
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• v.10 no.10
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• pp.277-282
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• 2012

The speech recognition system can not quickly adapt to varied environmental noise factors that degrade the performance of recognition. In this paper, the echo noise robust HMM learning model using average estimator LMS algorithm is proposed. To be able to adapt to the changing echo noise HMM learning model consists of the recognition performance is evaluated. As a results, SNR of speech obtained by removing Changing environment noise is improved as average 3.1dB, recognition rate improved as 3.9%.