• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.1
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• pp.39-49
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• 2020

In this paper, we show that the Chinese standard block cipher SM4 is vulnerable to the side channel attacks and present a countermeasure to resist them. We firstly validate that the secret key of SM4 can be recovered by differential power analysis(DPA) and correlation power analysis(CPA) attacks. Therefore we analyze the vulnerable element caused by power attack and propose a first order masking-based countermeasure to defeat DPA and CPA attacks. Although the proposed countermeasure unfortunately is still vulnerable to the profiling power attacks such as deep learning-based multi layer perceptron(MLP), it can sufficiently overcome the non-profiling attacks such as DPA and CPA.

• The Journal of the Acoustical Society of Korea
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• v.43 no.2
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• pp.253-259
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• 2024

This paper proposes a new speech enhancement model based on a complex nested U-Net with a dual-branch decoder. The proposed model consists of a complex nested U-Net to simultaneously estimate the magnitude and phase components of the speech signal, and the decoder has a dual-branch decoder structure that performs spectral mapping and time-frequency masking in each branch. At this time, compared to the single-branch decoder structure, the dual-branch decoder structure allows noise to be effectively removed while minimizing the loss of speech information. The experiment was conducted on the VoiceBank + DEMAND database, commonly used for speech enhancement model training, and was evaluated through various objective evaluation metrics. As a result of the experiment, the complex nested U-Net-based speech enhancement model using a dual-branch decoder increased the Perceptual Evaluation of Speech Quality (PESQ) score by about 0.13 compared to the baseline, and showed a higher objective evaluation score than recently proposed speech enhancement models.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.6C
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• pp.770-776
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• 2004

The goal of perceptual audio coder is to reduce redundancy and irrelevancy of audio signal based on the concept of masking. Several studies on masking effect reveal that the masking threshold varies as a function of the noise-like or tone-like nature of audio signals. Therefore, tonality of audio signal influences significantly the quality and efficiency of perceptual audio coder In this paper, we propose a new effective algorithm for tonality measure using spectrum energy. Since the proposed algorithm consists of a few transcendental functions and simple operations, it has lower complexity than MPEG psychoacoustic model-II. The proposed algorithm was tested with some audio signals, and DSP implementation showed that the proposed algorithm could be implemented with 3 MIPS. These results illustrate the efficiency of proposed algorithm in both performance and complexity.

• The Journal of the Acoustical Society of Korea
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• v.26 no.7
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• pp.323-327
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• 2007

In this paper, objectively quantified consonance of complex sound is proposed as a new psychoacoustical parameter. Proposing algorithm quantifies consonance of complex sound after applying psycho acoustical models which are parts of human perception such as masking effect, equal loudness contour, and critical band. To verify proposing algorithm, experiments with 10 car horn signals which have different complex sound were performed. The experiments show cross correlation of 0.95 between objectively quantified consonance by proposing algorithm and subjectively assessed consonance by listening tests. Considering the fact that there are few psychoacoustical parameter except Zwicker parameter, proposing algorithm will help to quantify psychoacoustical effect of complex sounds objectively.

• 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.

• Proceedings of the KSPS conference
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• 2003.05a
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• pp.215-218
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• 2003

In this paper we apply PMC (parallel model combination) to speech recognition system online. As a representative of model based noise compensation techniques, PMC compensates environmental mismatch by combining pretrained clean speech models and real-time estimated noise information. This is very effective approach for compensating extreme environmental mismatch but is inadequate to use in on-line system for heavy computational cost. To reduce the computational cost and to apply PMC online, we use a noise masking effect - the energy in a frequency band is dominated either by clean speech energy or by noise energy - in the process of model compensation. Experiments on artificially produced noisy speech data confirm that the proposed technique is fast and effective for the on-line model compensation.

• Annual Conference on Human and Language Technology
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• 2021.10a
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• pp.509-513
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• 2021

개체명 인식이란, 문장에서 인명, 지명, 기관명, 날짜, 시간 등의 고유한 의미의 단어를 찾아서 미리 정의된 레이블로 부착하는 것이다. 일부 단어는 문맥에 따라서 인명 혹은 기관 등 다양한 개체명을 가질 수 있다. 이로 인해, 개체명에 대한 중의성을 가지고 있는 단어는 개체명 인식 성능에 영향을 준다. 본 논문에서는 개체명에 대한 중의성을 최소화하기 위해 사전을 구축하여 ELECTRA 기반 모델에 적용하는 학습 방법을 제안한다. 또한, 개체명 인식 데이터의 일반화를 개선시키기 위해 동적 마스킹을 이용한 데이터 증강 기법을 적용하여 실험하였다. 실험 결과, 사전 기반 모델에서 92.81 %로 성능을 보였고 데이터 증강 기법을 적용한 모델은 93.17 %로 높은 성능을 보였다. 사전 기반 모델에서 추가적으로 데이터 증강 기법을 적용한 모델은 92.97 %의 성능을 보였다.

• Proceedings of the Acoustical Society of Korea Conference
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• 1998.08a
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• pp.60-64
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• 1998

음성인식 시스템의 실용화 과정에서 훈련환경과 테스트 환경의 불일치로 인한 인식성능의 저하는 반드시 극복되어야 할 문제이다. 본 논문에서는 잡음 tR인 입력음성의 비음성구간에서 잡음레벨을 추정하여 음성 스펙트럼에서 추정된 잡음레벨을 빼는 스펙트럼 차감법고 스펙트럼 영역에서 미리 정해진 마스킹 레벨보다 낮은 에너지 값을 마스킹 레벨로 올려주는 잡음 마스킹을 함께 사용함으로써 훈련 환경과 테스트환경의 불일치를 줄이는 방법을 제안한다. 그리고 복수의 마스킹 레벨에 대한 모델들을 미리 만들어 두고 추정된 잡음 레벨에 따라 적합한 마스킹 레벨의 보델을 사용하여 인식을 수해？는 다중 모델 방법을 적용하였다. 자동차 소음환경에서 두 가지 마스킹 레벨에 대한 모델을 이용한 화자독립고립단어 인식 실험을 통하여 본 논문에서 제안한 방식은 정차중 무시동 환경에서 95.8%, 정차중 시동 환경에서 95.6%, 한적한 도로환경에서 92.8%, 복잡한 시내도로 환경에서 89.6%, 고속도로 환경에서 74.4%의 인식성능을 나타내었으며, 평균 90.7%의 성능을 얻을 수 있다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.17 no.2
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• pp.159-167
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• 1992

This paper describes a feature extraction process by using a multi-layer neural network and is applied to the Korean stroke pattern for on line hand written character recognition, In the first layer the features are detected during the writing process and in the second layer the stroke specific features are extracted. A modified Masking field algorithm for direction co9nstancy has been used in this neural network and the resulting action potential of stroke specific features represents statistical distribution of the features in the on-line input stroke pattern and these results can be used in the recognition of on-line hand written Korean characters successfully.

• The Journal of the Acoustical Society of Korea
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• v.25 no.7
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• pp.325-332
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• 2006

In this paper. we Propose the noise suppressor with the Perceptual model and wavelet packet transform. The objective is to enhance speech corrupted colored or non-stationary noise. If corrupted noise is colored. subband approach would be more efficient than whole band one. To avoid serious residual noise and speech distortion, we must adjust the Wavelet Coefficient Threshold (WCT). In this Paper. the subband is designed matching with the critical band and WCT is adapted noise masking threshold (NMT) and segmental signal to noise ratio (seg_SNR). Consequently. it has similar Performance with EVRC in PESQ-MOS. But it's better than wavelet packet transform using universal threshold about 0.289 in PESQ-MOS. The important thing is that it's more useful than EVRC in coded speech. In coded speech. PESQ-MOS is higher than EVRC about 0.23.