• 한국산학기술학회논문지
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• 제15권5호
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• pp.2623-2627
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• 2014

본 연구의 목적은 우퍼 스피커 유닛의 열전달 특성 고찰하기 위하여 입력신호를 500Hz, 1000Hz, 2000Hz 그리고 3000Hz로 변화시키면서 실험을 수행하였다. 이를 위하여, 우퍼 스피커 유닛의 더스트 캡을 제거하고 보빈 내부에 열전대를 부착하여 보이스 코일에서 발생되는 온도를 측정하였고 주변으로의 열전달 특성을 파악하였다. 결과적으로, 입력신호가 감소할수록 보이스 코일 온도가 증가하였고, 입력신호가 증가할수록 스피커 유닛 각 부품의 온도편차가 증가하는 것을 확인하였다. 또한 1800sec및 입력신호 500Hz에서 보이스 코일 온도는 3000Hz에 비하여 48.4% 감소하였다.

• 한국지능시스템학회논문지
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• 제16권6호
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• pp.671-676
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• 2006

일반적으로 가상 스피커 구현을 위한 음상정위 방법으로 HRTF(Head Related Transfer Function) DB를 원음에 convolution하는 기법을 사용하게 된다. 그러나 비개인화된 HRTF는 가상 스피커 구현에 있어 사용자에 따라 상/하 또는 앞/뒤 방향에 대해서 혼돈을 가져올 수 있어 정위감을 저하시킬 수 있다. 본 논문에서는 상/하, 앞/뒤 정위감을 개선하기 위해 가상 스피커 주변의 HRTF를 그룹화하여 만들어진 새로운 HRTF를 사용한 가상 스피커에 대하여 연구한다. 효과적인 HRTF 그룹화를 위해 필요한 HRTF 개수, 위치 등을 실험을 통해 결정하며, 청감 평가를 수행한다. 생성된 HRTF를 사용한 가상 스피커의 성능 평가 결과, 상/하, 앞/뒤 정위감이 개선됨을 실험을 통해 확인하였다.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 1998년도 추계종합학술대회 논문집
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• pp.1223-1226
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• 1998

The pre-emephasis filter as the conventional method emphasizes all components of high frequency that reflects the speaker characteristics. However this filter don't show the auditory characteristics of speaker's speech. In order to emphasize the perceptual characteristics, we propose the speaker recognition system that uses the perceptual weighting as the preprocessor because the Auditory characteristic of human is sensitive to the formant peaks. This filter has the characteristcs that both deemphasizes the low-formants and emphasizes the high formants. As a result of the proposed method, we improve the total recognition rate 1.7% better than the conventional method.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2000년도 제13회 신호처리 합동 학술대회 논문집
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• pp.157-160
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• 2000

In the generally a voice conversion has used VQ(Vector Quantization) for partitioning the spectral feature and has performed by adding an appropriate offset vector to the source speaker's spectral vector. But there is not represented the target speaker's various characteristics because of discrete characteristics of transformed parameter. In this paper, these problems are solved by using the LMR(Linear Multivariate Regression) instead of the mapping codebook which is determined to the relationship of source and target speaker vocal tract characteristics. Also we propose the method for solved the discontinuity which is caused by applying to time aligned parameters using Dynamic Time Warping the time or pitch-scale modified speech. In our proposed algorithm for overcoming the transitional discontinuities, first of all, we don't change time or pitch scale and by using the LMR change a speaker's vocal tract characteristics in speech with non-modified time or pitch. Compared to existed methods based on VQ and LMR, we have much better voice quality in the result of the proposed algorithm.

• 음성과학
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• 제15권3호
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• pp.7-15
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• 2008

This paper proposes the method to extract new feature vectors using the difference between the cepstrum for static characteristics and delta cepstrum for dynamic characteristics in speaker recognition (SR). The difference vector (DV) which it proposes from this paper is containing the static and the dynamic characteristics simultaneously at the intermediate characteristic vector which uses the deference between the static and the dynamic characteristics and as the characteristic vector which is new there is a possibility of doing. Compared to the conventional method, the proposed method can achieve new feature vector without increasing of new parameter, but only need the calculation process for the difference between the cepstrum and delta cepstrum. Experimental results show that the proposed method has a good performance more than 2.03%, on average, compared with conventional method in speaker identification (SI).

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2010년도 춘계학술대회 논문집
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• pp.1247-1248
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• 2010

• 한국수산과학회지
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• 제44권5호
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• pp.543-549
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• 2011

An underwater speaker was developed for use as an acoustic deterrent device that transmits acoustic energy through the water omnidirectionally over a broadband frequency range to eliminate marine mammal attacks and to prevent physical damage to the inshore and coastal fishing grounds of Korea. The underwater speaker was constructed of two vibration caps machined from 6061-T6 aluminum alloy and a stack of PZ 26 piezoelectric ceramic rings (Ferroperm Piezoceramics A/S) connected mechanically in series and electrically in parallel. The performance characteristics of the underwater speaker were measured and analyzed in an experimental water tank of $5\;m{\times}5\;m{\times}6\;m$. The peak transmitting voltage response (TVR) was measured at 11.16 kHz with 163.45 dB re $1\;{\mu}Pa$/V at 1m. The underwater speaker showed a near omnidirectional beam pattern at the peak TVR resonance frequency. The usable frequency range was 4-25 kHz with a lower TVR limit of approximately 140 dB. We conclude that this underwater speaker could be satisfactorily used as an acoustic deterrent device against marine mammals, particularly the bottlenose dolphin, to protect catches and fishing grounds as well as the mammals themselves, for example, by keeping them away from fishing gear and/or vessels.

• The Journal of the Acoustical Society of Korea
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• 제21권4E호
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• pp.156-163
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• 2002

We apply independent component analysis (ICA) for extracting an optimal basis to the problem of finding efficient features for representing speech signals of a given speaker The speech segments are assumed to be generated by a linear combination of the basis functions, thus the distribution of speech segments of a speaker is modeled by adapting the basis functions so that each source component is statistically independent. The learned basis functions are oriented and localized in both space and frequency, bearing a resemblance to Gabor wavelets. These features are speaker dependent characteristics and to assess their efficiency we performed speaker identification experiments and compared our results with the conventional Fourier-basis. Our results show that the proposed method is more efficient than the conventional Fourier-based features in that they can obtain a higher speaker identification rate.

• 한국음향학회지
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• 제19권8호
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• pp.63-67
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• 2000

본 논문에서는 화자인식의 성능향상을 위한 dynamic time warping (DTW) 기반의 문맥 제시형 화자인식에 대해 연구하였다. 화자인식에 있어 중요한 요소인 화자의 특성을 잘 반영할 수 있는 참조패턴을 생성하기 위해 유전자 알고리즘을 적용하였다. 또한, 문맥 종속형과 문맥 독립형 화자인식의 단점을 개선하기 위해 문맥 제시형 화자인식을 수행하였다. Clos set에서 화자식별과 open set에서 화자확인 실험을 하였으며 실험결과 기존 방법의 참조패턴을 이용하였을 경우보다 유전자 알고리즘에 의한 참조패턴이 인식률과 인식속도 면에서 우수함을 보였다.

• 한국음향학회지
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• 제21권4호
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• pp.156-156
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• 2002

We apply independent component analysis (ICA) for extracting an optimal basis to the problem of finding efficient features for representing speech signals of a given speaker The speech segments are assumed to be generated by a linear combination of the basis functions, thus the distribution of speech segments of a speaker is modeled by adapting the basis functions so that each source component is statistically independent. The learned basis functions are oriented and localized in both space and frequency, bearing a resemblance to Gabor wavelets. These features are speaker dependent characteristics and to assess their efficiency we performed speaker identification experiments and compared our results with the conventional Fourier-basis. Our results show that the proposed method is more efficient than the conventional Fourier-based features in that they can obtain a higher speaker identification rate.