인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 저자정보
초록·키워드
Below 4.8 kbits/s, code-excited linear predictive(CELP) coders in general suffer from two kinds of perceptually important degradation. One is noise between adjacent harmonics of output speech, that is, inter-harmonic noise, which results in roughness in voiced sound. The other is poor reproduction of speech signal at high frequencies, that is, high frequency mismatch. Several approaches have been introduced to remedy these degradations. These approaches, however, are known to be inadequate for the perceptually weighted mean-squared error criterion typically used in the conventional CELP coder. In order to get the quality as best as possible particularly at a low rate, we propose in this paper an improved weighting function which utilizes the spectral weighting methodology and also takes into account the periodic character in voiced sound. The proposed weighting function can adapt to variation of pitch by itself without any pitch estimation in voiced sound and is also applicable to all speech segments without any voiced/unvoiced discrimination algorithm. Simulation results show that the performance of the CELP coder with the proposed weighting function is better than that of the conventional CELP coder.
본문·목차
인공지능 문자 인식 모델을 통해 추출된 텍스트로, 일부 오타나 오류가 포함될 수 있으나 지속적으로 개선 중입니다.
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오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
최근 본 자료 전체보기
UCI(KEPA) : I410-ECN-0101-2009-560-018974901