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결정적/확률적 요소로의 음성 분해와 심리음향 모델 기반 잡음 제거 기법
조석환(Seokhwan Jo),유창동(Chang D. Yoo) 대한전자공학회 2007 대한전자공학회 학술대회 Vol.2007 No.7
A speech enhancement algorithm based on both a decomposition of speech into deterministic and stochastic components and a psychoacoustic model is proposed. Noisy speech is decomposed into deterministic and stochastic components, and then each component is enhanced preserving its individual characteristics. A psychoacoustic model is taken into account when enhancing the stochastic component. Simulation results show that the proposed algorithm performs better than some of the more popular algorithms.
임베디드 디바이스에서 음성 인식 알고리듬 구현을 위한 부동 소수점 연산의 고정 소수점 연산 변환 기법
윤성락(Sungrack Yun),유창동(Chang D. Yoo) 대한전자공학회 2007 대한전자공학회 학술대회 Vol.2007 No.7
This paper proposes an automatic conversion method from floating-point value computations to fixed-point value computations for implementing automatic speech recognition (ASR) algorithms in embedded device.
로그 우도 차이의 p-norm에 기반한 은닉 마르코프 파라미터 추정 알고리듬
윤성락(Sungrack Yun),유창동(Chang D. Yoo) 대한전자공학회 2007 대한전자공학회 학술대회 Vol.2007 No.7
This paper proposes a discriminative training algorithm for estimating hidden Markov model (HMM) parameters. The proposed algorithm estimates the parameters by minimizing the p-norm of log-likelihood difference (PLD) between the utterance probability given the correct transcription and the most competitive transcription.
얼굴 색상 필터링과 Adaboost 알고리즘을 결합한 효율적인 얼굴 검출 알고리즘
박상혁(Sanghyuk Park),유창동(Chang D. Yoo) 대한전자공학회 2010 대한전자공학회 학술대회 Vol.2010 No.6
In this paper, we propose face detection method by combining skin color filtering and Adaboost method for efficient face detection system. By using skin color filtering, it can reduce candidate face regions Efficiently. Experimental results are comparable with results of previous Adaboost methods. According to experimental results, The proposed method is good enough method with high detection accuracy while it reduce false alarm rate compare to conventional method.
K-최근방 이웃 방법을 사용한 장면 분류 시스템의 문턱값 접근을 통한 실제 환경에서의 성능 향상 방법
백승렬(SeungRyul Baek),유창동(Chang. D. Yoo) 대한전자공학회 2010 대한전자공학회 학술대회 Vol.2010 No.6
An Input image is blocked into several blocks and features are extracted from these blocks. Blocks are classified by K-NN classifier using training data with predefined labels, and the most frequently selected block label becomes the label of the image. K-NN based scene classification system is not perfect in a practical situation because there are lots of ambiguous images which even a man cannot tell (indoor from outdoor), (city from landscape), (sunset from mountain&forest), (forest from mountain). Thresholding approach is added to explicitly say that ambiguity exists, and this image has ambiguous label. This increases performance and completeness of previous K-NN based scene classification system.
심리음향적 제약조건 최적화에 기반한 잡음 제거 기법 문제 설정 및 고찰
조석환(Seokhwan Jo),유창동(Chang D. Yoo) 대한전자공학회 2010 대한전자공학회 학술대회 Vol.2010 No.6
This paper considers a speech enhancement based on the psychoacoustically constrained optimization problem. In this paper, four constrained optimization problems are set using the masking threshold of the clean speech, and these problems and their solutions are considered. Experimental results show that the performance of the algorithms considered in this paper.