• The Journal of the Acoustical Society of Korea
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• v.22 no.5
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• pp.351-359
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• 2003

In this paper, we proposed a method for acoustic echo cancellation based on independent component analysis. When the large acoustic noise is picked up by the microphone, the performance of echo cancellation decreased. We used two microphones that received echo signal which is linearly mixed with the noise, then separated the echo signals from the received signals with independent component analysis algorithm. The separated echo signal is used for the reference signal of adaptive algorithm which leads to better performance of the echo cancellation. Computer simulation results show the validity of the proposed method.

• Proceedings of the IEEK Conference
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• 2000.09a
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• pp.7-10
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• 2000

This paper focuses on the development of speech enhancement techniques for hands-free audio terminals, including two major problems : noise cancellation and acoustic echo cancellation. The objective is to find a joint structure to get a near-end speech signal with minimum distortion and low levels of echo and noise. To solve the two problems, a new promising technique is studied and tested in computer simulation conditions.

• Journal of Digital Convergence
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• v.10 no.11
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• pp.377-382
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• 2012

In this paper, the echo noise robust CHMM learning model using echo cancellation average estimator LMS algorithm is proposed. To be able to adapt to the changing echo noise. For improving the performance of a continuous speech recognition, CHMM models were constructed using echo noise cancellation average estimator LMS algorithm. As a results, SNR of speech obtained by removing Changing environment noise is improved as average 1.93dB, recognition rate improved as 2.1%.

• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.416-418
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• 2006

In this paper, a new acoustic echo cancellation approach based on the DUET algorithm and scaling factor estimation is proposed to solve the scaling ambiguity in case of blind separation based acoustic echo cancellation in a noisy environment. In hands-free full-duplex communication system. acoustic noises picked up by the microphone are mixed with echo signal. For this reason, the echo cancellation system may provide poor performance. For that purpose, a degenerate unmixing estimation technique, adjusted in the time-frequency domain, is employed to separate undesired echo signals and noises. Also, since scaling and permutation ambiguities have not been solved in the blind source separation algorithm, kurtosis for the desired signal selection and a scaling factor estimation algorithm are utilized in this rarer for the separation of an echo signal. Simulation results demonstrate that the proposed approach yields better echo cancellation and noise reduction performances, compared with conventional methods.

• The Journal of the Acoustical Society of Korea
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• v.18 no.2E
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• pp.45-52
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• 1999

This paper presents the integrated speech enhancement system for hands-free mobile communication. The proposed integrated system incorporates both acoustic echo cancellation and engine noise reduction device to provide signal enhancement of desired speech signal from the echoed plus noisy environments. To implement the system, a delayless subband adaptive structure is used for acoustic echo cancellation operation. The NLMS based adaptive noise canceller then applied to the residual echo removed noisy signal to achieve the selective engine noise attenuation in dominant frequency component. Two sets of computer simulations are conducted to demonstrate the effectiveness of the system; one for the fixed acoustical environment condition, the other for the robustness of the system in which, more realistic situation, the acoustic transmission environment change. Simulation results confirm the system performance of 20-25dB ERLE in acoustic echo cancellation and 9-19 dB engine noise attenuation in dominant frequency component for both cases.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.3
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• pp.629-631
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• 2007

In hands-free full-duplex communication systems, acoustic signals picked up by the microphones can be mixed with echo signals as well as noises, which may result in poor performance of the corresponding communication system. Also, the system performance may decrease further if the reverberation occurs since it is harder to estimate the impulse response of the demixing system. For blind source separation (BSS) in such cases, a time-frequency masking approach can be employed to separate undesired echo signals and noises, but, permutation ambiguities also should be solved for the echo cancellation. In this paper, we propose a new acoustic echo cancellation (AEC) approach utilizing the time-frequency masking and higher-order statistics, whereby a desired signal selection, based on coherence and third-order statistics (i.e., kurtosis), is introduced along with output signal normalization. Simulation results demonstrate that the proposed approach yields better echo and noise cancellation performances than the conventional AEC approaches.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.05a
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• pp.839-842
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• 2010

In this paper, we propose a residual echo and noise reduction scheme for hands-free telephony applications. The proposed algorithm uses a noise robust modified AP algorithm which estimate well echo path in noisy and whitens residual echo signal using linear prediction at non double-talk duration. It is confirmed that the proposed algorithm shows better performance from acoustic interference cancellation (AIC) viewpoint.

• 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).

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2003.05a
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• pp.645-651
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• 2003

The system in which a microphone and a loudspeaker are simultaneously used can cause an echo. The echo is caused by feedback between the output of the loudspeaker and the input of the microphone. The acoustic echo canceller is a device to cancel the echo in a communication system. Its general procedure for cancellation is first estimating the plant response of the feedback path and then eliminating the feedback signal from the input signal. In this paper, full-band and sub-band approaches are compared by using some simulation examples.

• Journal of information and communication convergence engineering
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• v.8 no.6
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• pp.640-644
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• 2010

When we talk with hands-free in a car or noisy lobby, the performance of the echo canceller degrade because background noise added to echo caused by the distance from mouth to microphone is relatively long. It gives a reason for necessity of noise-robust and high convergence speed adaptive algorithm. And if acoustic echo canceller operated not perfectly, residual signal going through the echo canceller to far-end speaker remains residual echo, which degrade quality of talk. To solve this problem, post-processing needed to remove residual echo ones more. In this paper, we propose a new acoustic echo canceller, which has noise robust and high convergence speed, linked with linear predictor as a post-processor. By computer simulation, it is confirmed that the proposed algorithm shows better performance from acoustic interference cancellation (AIC) viewpoint.