• The Journal of the Acoustical Society of Korea
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• v.29 no.6
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• pp.402-409
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• 2010

In this paper, we propose an efficient integrated suppression algorithm based on combined power of acoustic echo and background noise. The proposed method combines the acoustic echo and noise power by the weighting parameter derived from the decision rule based on the estimated echo to noise power ratio. Therefore, in the proposed approach, the acoustic echo and noise signal are able to be reduced through only one suppression filter based on the estimated combined power. The proposed unified structure improves the problems of the residual echo and noise resulted from the conventional unified structure where the noise suppression (NS) operation is placed after the acoustic echo suppression (AES) algorithm or vice versa. The performance of the proposed algorithm is evaluated by the objective test under various environments and yields better results compared with the conventional scheme.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.10C
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• pp.955-960
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• 2009

In this paper, we propose a novel approach to residual echo suppression (RES) algorithm based on tracking echo-presence uncertainty (TEPU) to improve the performance of acoustic echo suppression (AES) in the frequency domain. In the proposed method, the ratio of the microphone input and the echo-suppressed output signal power is employed as the threshold value for the decision rule to estimate the echo-presence uncertainty applied to the RES filter. The proposed RES scheme estimates the echo presence uncertainty in each frequency bin and effectively reduces residual echo signal in a simple fashion. The performance of the proposed algorithm is evaluated by the objective test and yields better results compared with the conventional schemes.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39C no.12
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• pp.1346-1351
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• 2014

We propose a novel approach for stereophonic acoustic echo suppression using spectro-temporal filtering based on soft decision. Unlike the conventional approaches estimating the echo pathes directly, the proposed technique can estimate stereo echo spectra without any double-talk detector. In order to improve the estimation of echo spectra, the extended power spectrum density matrix and echo overestimation control matrix are applied on this method. In addition, this echo suppression technique is based on soft decision technique using speech absence probability in STFT domain. Experimental results show that the proposed method improves compared with the conventional approaches.

• 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.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.5
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• pp.162-166
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• 2009

In this paper, we propose a novel approach of an acoustic echo cancellation (AEC) algorithm which is differently adopted in the relevant period condition by the suppression parameter of a parametric wiener filter (PWF). The PWF uses the suppression parameter to compensate uncertainty of acoustic echo signal estimation. The existing PWF method using the fixed suppression parameter derives the distortion of the near-end signal at the double-talk. To solve this problem, the boundary condition is devised using decision of the double-talk detection (DTD) algorithm and voice activity detector (VAD). The boundary condition makes it possible to treat differently depending on the case of the single-talk and double-talk. According to the experimental results, the proposed approach is found to be effective for acoustic echo cancellation using the boundary condition.

• The Journal of the Acoustical Society of Korea
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• v.28 no.3
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• pp.285-289
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• 2009

In this paper, we propose a novel double-talk detection (DTD) technique based on soft decision in the frequency domain. In the proposed method, global near-end speech presence probability (GNSPP) considering the statistical model assumption and voice activity detection (VAD) decision of the near-end and far-end signal are applied to the DTD algorithm in the frequency domain instead of the traditional hard decision scheme using cross-correlation coefficients. The performance of the proposed algorithm is evaluated by the objective test under various environments, and yields better results compared with the conventional scheme.

• The Journal of the Acoustical Society of Korea
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• v.27 no.1E
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• pp.17-24
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• 2008

Blind speech separation (BSS) is well-known as a powerful technique for speech enhancement in many real world environments. In this paper, we propose a new application of BSS - acoustic echo cancellation (AEC) in a car environment. For this purpose, we develop a block-online BSS algorithm which provides robust separation than a batch version in changing environments with moving speakers. Simulation results using real world recordings show that the block-online BSS algorithm is very robust to speaker movement. When combined with AEC, simulation results using real audio recording in a car confirm the expectation that BSS improves double talk detection and echo suppression.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.44 no.4
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• pp.413-422
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• 2011

An improved split-beam transducer for a 50 kHz fish-sizing echo sounder was developed. The main objective of this study was to minimize the side lobe level in the beam pattern and the distance between acoustic centers for adjacent transducer quadrants in the geometrical arrangement of array elements while maintaining a given number of transducer elements and beam width. To achieve these goals, a 32-element planar array transducer ($6{\times}6$ array with one element in each corner missing) was designed using the Dolph-Chebyshev shading function to suppress side lobes in the array beam pattern and fabricated by arranging the inter-element spacing to be substantially equal to half the wavelength using the transducer element of 0.4 times the wavelength in diameter. The performance characteristics of this split-beam transducer were evaluated in the experimental water tank of $5m{\times}5m{\times}6m$ (length${\times}$height${\times}$width). In this study, the design goal of the beam width and side lobe level for transmitting a beam pattern was initially set at $21^{\circ}$ and -30 dB, respectively. However, the measured beam width at 3 dB was $21^{\circ}$ in both directions with side lobe levels of -24.7 dB in the horizontal plane and -25.6 dB in the vertical plane. The averaged beam width at -3 dB of the receiving beam patterns for four receiving quadrants was $31.4^{\circ}$. The transmitting voltage response was 161.5 dB (re $1{\mu}Pa$/V at 1 m) at 50.23 kHz with a bandwidth of 2.16 kHz, and the averaged receiving sensitivity for four receiving quadrants was -178.13 dB (re 1 V/${\mu}Pa$) at 49.8 kHz with a bandwidth of 2.64 kHz.

• 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.