• Journal of the Institute of Convergence Signal Processing
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• v.4 no.3
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• pp.15-20
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• 2003

For some applications such as teleconference or telecommunication systems using a distant-talking hands-free microphone, the near-end speech signals to be transmitted is disturbed by an ambient noise and by an echo which is due to the coupling between the microphone and the loudspeaker. Furthermore, the environmental noise including channel distortion or additive noise is assumed to affect the original input speech. In the present paper, a new approach using echo canceller and maximum a posteriori(MAP) estimation is introduced to improve the accuracy of hands-free speech recognition. In this approach, it was shown that the proposed system was effective for hands-free speech recognition in ambient noise environment including echo. The experimental results also showed that the combination system between echo canceller and MAP environmental adaptation technique were well adapted to echo and noise environment.

• 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.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.2
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• pp.366-373
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• 2007

In this paper we propose a multi-channel speech pickup system for calling quality enhancement of hands-free communication using ALTERA Nios-II processor. Multi-channel speech pickup system uses Delay-and-Sum beamformer with zero-padding interpolator. This paper implements speech pickup system using the Nios-II processor with real-time I/O data processing speed. The proposes speech pickup embedded system shows a good agreement with those of computer simulation(MATLAB) and conventional DSP processor(TMS320C6711) result. The proposed method is effective more than previous methods in cost and design processing time. As a result, LE(Logic Element) of hardware used 3,649/5,980(61%) on a chip.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.05a
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• pp.784-788
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• 2008

In this research, we propose a remote speech input unit, a new method of user-friendly speech input in speech recognition system. We focused the user friendliness on hands-free and microphone independence in speech recognition applications. Our module adopts two algorithms, the automatic speech detection and speech enhancement based on the microphone array-based beamforming method. In the performance evaluation of speech detection, within-200msec accuracy with respect to the manually detected positions is about 97percent under the noise environments of 25dB of the SNR. The microphone array-based speech enhancement using the delay-and-sum beamforming algorithm shows about 6dB of maximum SNR gain over a single microphone and more than 12% of error reduction rate in speech recognition.

• 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.

• 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.

• The Journal of the Acoustical Society of Korea
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• v.17 no.2E
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• pp.38-46
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• 1998

In this paper, we propose a remote speech input device, a new method of user-friendly speech input in spontaneous speech recognition system. We focus the user friendliness on hands-free and microphone independence in speech recognition applications. Our method adopts two algorithms, the automatic speech detection and the microphone array delay-and-sum beamforming (DSBF)-based speech enhancement. The automatic speech detection algorithm is composed of two stages; the detection of speech and nonspeech using the pitch information for the detected speech portion candidate. The DSBF algorithm adopts the time domain cross-correlation method as its time delay estimation. In the performance evaluation, the speech detection algorithm shows within-200 ms start point accuracy of 93%, 99% under 15dB, 20dB, and 25dB signal-to-noise ratio (SNR) environments, respectively and those for the end point are 72%, 89%, and 93% for the corresponding environments, respectively. The classification of speech and nonspeech for the start point detected region of input signal is performed by the pitch information-base method. The percentages of correct classification for speech and nonspeech input are 99% and 90%, respectively. The eight microphone array-based speech enhancement using the DSBF algorithm shows the maximum SNR gaing of 6dB over a single microphone and the error reductin of more than 15% in the spontaneous speech recognition domain.

• 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 KSPS conference
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• 2005.11a
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• pp.151-154
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• 2005

원거리 음성인식에서 인식률의 성능향상을 위해 필수적인 다채널 마이크 환경에서 방 안의 도처에 분산되어있는 원거리 마이크를 사용하여 TV, 조명 등의 주변 환경을 음성으로 제어하고자 한다. 이를 위해 각 채널의 인식결과를 통합하여 최적의 결과를 얻고자 채널의N-best 결과와 N-best 결과에 포함된 hypothesis의 frame-normalized likelihood 값을 사용하여 Bayesian network을 훈련하고 인식결과를 통합하여 최선의 결과를 decision 하는데 사용함으로써 원거리 음성인식의 성능을 향상시키고 또한 hands-free 응용을 현실화하기위한 방향을 제시한다.

• Journal of IKEEE
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• v.13 no.2
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• pp.132-139
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• 2009

In this paper, a speech feature based double-talk detector method is proposed for an acoustic echo cancellation in hands-free communication system. The double-talk detector is an important element, since it controls the update of the adaptive filter for an acoustic echo cancellation. In previous research, the double talk detector is considered in the signal processing stage without taking the speech characteristics into account. However, in the proposed method, speech features which are used for the speech recognition is used for the discriminative features between the far-end and near-end speech. We obtained a substantial improvement over the previous double-talk detector methods using the only signal in time domain.