• The Journal of the Acoustical Society of Korea
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• v.17 no.3
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• pp.59-64
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• 1998

본 논문에서는 LSP 벡터 양자화의 성능에 대하여 분석하고 성능이 향상된 새로운 LSP 벡터 양자화 방법을 제안한다. 먼저, 10msec프레임 구조를 가지고 Moving Average 예측 필터를 사용한 LSP Split 벡터 양자화의 성능을 여러 훈련 방법과 벡터 Split 방법 및 Bit 할당 방법에 따라 비교한다. 다음, Split 벡터 양자화의 문제점을 해결하기 위하여 새로 운 Split 벡터 양자화 검색 방법을 제안한다. 스펙트럼 왜곡지수를 이용한 양자화 성능 측정 결과 새로 제안된 방법이 기존의 방법보다 우수한 양자화 성능을 보인다.

• The Journal of the Acoustical Society of Korea
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• v.11 no.1E
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• pp.73-78
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• 1992

시벼형 신호인 음성 신호의 분석에 칼만필터를 이용하였다. 일반적인 음성 분석은 프레임단위의 처리방법인 선형 예측 부호화 기법을 주로 이용하지만 음성의 시변 특성을 파악하는데에는 적절하지 못 하다. 따라서 순차적인 추정기법으로 많이 이용되는 칼만 필터를 음성 분석에 적용하였다. 또한 음성과 같은 시변신호에서는 과거 신호의 잡음의 분산값에 적당한 가중치를 부가하므로써 과거의 신호에 의해 서 현재의 추정값에 미치는 영향을 줄였으며 이를 음성의 천이 구간에서의 파라메타 추정에 사용하였 다. 그리고 음성신호 모델에서 생기는 모델링 오차는 일반적으로 백색 가우시안 잡음으로 가정하고 있 으나 이는 자음과 같은 무성음에서 특징 파라메타 푸정에는 오차가 적지만 모음등의 유성음에서는 음성 발생시의 여기신호인 펄스열에 의해서 많은 모델링 오차를 생기게 한다. 따라서 모델링 오차신호는 Non-Gaussian 확률분포로 가정한 후 로버스트 칼만 필터를 사용하여 합성으멩 대해 특징 파라메터를 추출하였다.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 1995.04a
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• pp.178-183
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• 1995

본 연구에서는 플랜트 잡음이 강한 음향 환경에서 기존의 인버스 필터링 방법에 적용 선형 증진기를 부착하여 부가경로 전달함수의 온라인 모델링과 주소음원에 대한 제어 시뮬레이션을 수행하여 다음과 같은 결과를 얻었다. 첫째로, 신호대 잡음비가 낮은 음향 환경에서 적응 선형 증진기를 이용하여 플랜트 잡음을 제거함으로써 부가경로 전달함수의 온라인 모델링을 수행할 수 있었다. 둘째로, 실제의 부가경로 전달함수가 변한 상태에서 제안된 알고리즘을 이용하여 제어 시뮬레이션을 수행하여 주소음원에 대한 제어와 정확하게 새로운 부가경로 전달함수를 예측할 수 있었다. 향후 본 연구에서 제안된 알고리즘을 실시간 어셈블리화하여 능동 소음 제어 실험한 결과를 발표할 예정이다.

• The Journal of the Acoustical Society of Korea
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• v.21 no.3
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• pp.285-292
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• 2002

One of the problems that should be solved in Text-To-Speech (TTS) is discontinuities at unit-joining points. To cope with this problem, a smoothing method using a low-pass filter is employed in this paper, In the proposed soothing method, a filter coefficient that controls the amount of smoothing is determined according to contort information to be synthesized. This method efficiently reduces both discontinuities at unit-joining points and artifacts caused by undesired smoothing. The amount of smoothing is determined with discontinuities around unit-joins points in the current synthesized speech and discontinuities predicted from context. The discontinuity predictor is implemented by CART that has context feature variables. To evaluate the performance of the proposed method, a corpus-based concatenative TTS was used as a baseline system. More than 6075 of listeners realized that the quality of the synthesized speech through the proposed smoothing is superior to that of non-smoothing synthesized speech in both naturalness and intelligibility.

• The Journal of the Acoustical Society of Korea
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• v.19 no.5
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• pp.65-70
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• 2000

It is blown that the loudness is one of the most important metrics in assessing the sound quality and a calculation method for loudness has been standardized for steady sounds. In this study, a new loudness model is suggested for dealing with the transient sound for a unified analysis of various practical sounds. A signal processing technique is introduced for this purpose, which is required for the band subdivision and the prediction of band-level change of transient sounds. In addition, models for the post-masking and the temporal integration are adopted in the analysis of the loudness of transient sounds. In order to solve the problem of the conventional loudness model in the pure-tone signal processing, a critical band filter is employed in the analysis, which consists of 47 critical filters having a filter spacing of a half of the critical bandwidth. For testing the effectiveness of the present model, the predicted responses are compared with the experimental data and it is observed that they are in good agreements.

• The Journal of the Acoustical Society of Korea
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• v.14 no.3
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• pp.90-96
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• 1995

A new method for autoregressive parameter estimation from noisy observation sequence is presented. This method, termed the AP method, is a result of an attempt to make use of the adaptive predictor which is a simple and reliable way of parameter estimation. It is shown theoretically that, for noisy input, the parameter vector computed from the prediction sequence is closer to that of the original sequence than the noisy input sequence is, under the spectral distortion criterion. Simulation results with the Kalman filter as a noise reduction filter and real speech data supported the theory. Roughly speaking, the performance of the parameter set obtained by the AP method is better than noisy one but worse than the EM iteration results. When the simplicity is considered, it could provide a useful alternative to more complicated parameter estimation methods in some applications.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2016.11a
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• pp.163-164
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• 2016

이전까지 많은 연구자들은 적응 신호처리(Adaptive Signal Process)를 이용한 잡음 제거 방법을 연구해 왔다. 그러나, 최근 발전하고 있는 멀티콥터는 프로펠러 모터의 RPM(Revolution Per Minute)이 실시간으로 변하기 때문에 적응 신호처리를 이용하여도 깔끔한 결과를 얻어 내기가 어렵다는 한계가 존재한다. 또한, 특정 주파수를 기준으로 형성되는 고조파(Harmonics)는 적응 알고리즘인 (N)LMS 를 이용한 예측에서 오차를 발생시키는 문제를 발생시킨다. 따라서, 본 논문에서는 멀티콥터를 이용한 음향 취득에 대한 소음 저감 방법으로 회전 속도계(Tachometer), 콤 필터(Comb Filter), NLMS 알고리즘(Normalized Least Mean Square Algorithm)을 이용한 방법을 제안한다.

• Journal of the Institute of Electronics Engineers of Korea TE
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• v.39 no.2
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• pp.44-50
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• 2002

Conventional acoustic echo cancelers using ES(Exponentially weighted Stepsize) algorithm have simple operational configuration and fast convergence speed batter then NLMS algorithm, but they are very weak in external noise because ES algorithm updates filter taps using an average energy reduction rate of room impulse response in specific acoustical condition. So, a new configuration of acoustic echo canceler with stepsize generator and selector is proposed in this thesis. The proposed stepsize generator and selector improve conventional acoustic echo canceler's weakness in external noise and improve the system robustness. The stepsize generator generates additional stepsize value using moving averager, which is the residual noise energy of error signal multiplied by constant ${\gamma}$. The stepsize selector selects the stepsize value that has better performance in an acoustic echo canceler using a coefficient decision factor ${\Delta}_{differ}$ The simulation results show that the proposed algorithm reduces residual error by 5[dB] to 10[dB], improves misadjustment regardless of external noise's SNR. 

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.6
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• pp.1249-1256
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• 2019

In this paper, we propose a new algorithm to remove acoustic feedback and noise in hearing aids. Instead of using the conventional FIR structure, this algorithm is a deep learning algorithm using neural network adaptive prediction filter to improve the feedback and noise reduction performance. The feedback canceller first removes the feedback signal from the microphone signal and then removes the noise using the Wiener filter technique. Noise elimination is to estimate the speech from the speech signal containing noise using the linear prediction model according to the periodicity of the speech signal. In order to ensure stable convergence of two adaptive systems in a loop, coefficient updates of the feedback canceller and noise canceller are separated and converged using the residual error signal generated after the cancellation. In order to verify the performance of the feedback and noise canceller proposed in this study, a simulation program was written and simulated. Experimental results show that the proposed deep learning algorithm improves the signal to feedback ratio(: SFR) of about 10 dB in the feedback canceller and the signal to noise ratio enhancement(: SNRE) of about 3 dB in the noise canceller than the conventional FIR structure.

• The Journal of the Acoustical Society of Korea
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• v.15 no.2
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• pp.90-94
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• 1996

Code Excited Linear Prediction(CELP) vocoder exhibits good performance at data rates below 8 kbps. The major drawback of CELP type coders is a large amount of computation. In this paper, we propose a new pitch searching method that preserves the quality of the CELP vocoder reducing computational complexity. The basic idea is that grasps preliminary pitches using the first formant of speech signal and performs pitch search only about the preliminary pitches. As applying the proposed method to the CELP vocoder, we can reduce complexity by 64% in the pitch search.