CAJ | 학술논문

基于单个麦克风的含噪语音信号频谱增强技术，一直受到有关工业和学术界的高度关注，其广泛应用于诸如语音识别、助听系统和免提终端通信等领域中。本文系统地讨论了含噪语音信号频谱增强系统设计的基本模块元素，并对诸如语音信号估计、语音信号出现概率估计、先验信噪比（SNR骷计和噪声功率谱估计等模块元素的统计技术与方法进行了较详细的讨论和描述。文中还讨论了含噪语音信号频谱增强算法的有关选择问题，并展望了其今后可能的研究与发展方向。
기우단개맥극풍적함조어음신호빈보증강기술，일직수도유관공업화학술계적고도관주，기엄범응용우제여어음식별、조은계통화면제종단통신등영역중。본문계통지토론료함조어음신호빈보증강계통설계적기본모괴원소，병대제여어음신호고계、어음신호출현개솔고계、선험신조비（SNR고계화조성공솔보고계등모괴원소적통계기술여방법진행료교상세적토론화묘술。문중환토론료함조어음신호빈보증강산법적유관선택문제，병전망료기금후가능적연구여발전방향。
The problem of spectral enhancement of noisy speech signals based on a single microphone has attracted considerable research effort for over 30 years. It is a problem with numerous applications ranging from speech recognition, to hearing aids and hands-free mobile communication. In this paper, the statistical methods are described and discussed for the fundamental components that constitute a noisy speech spectral enhancement system. In Section 2, the problem of speech spectral enhancement is formulated mathematically. Then, the time-frequency correlations of spectral coefficients for speech and noise signals are addressed and the statistical models are presented that confirm with these characteristics in Section 3. In Section 4, some estimators are given for speech spectral coefficients under speech presence uncertainty based on various fidelity criteria. The problem of speech presence probability estimation is addressed in Section 5. The useful estimators such as decision-directed approach and the recursive estimation approach for the a priori signal-to-noise ratio （SNR） under speech presence uncertainty are presented in Section 6. In additions, some typical and useful estimators for noise power spectrum are described in Section 7. In Section 8, the main types of spectral enhancement components are surveyed, and the significance of the choice of the statistical model, fidelity criterion, a priori SNR estimator, and noise spectrum estimator is discussed as well. Finally, some concluding comments and the future are made and discussed in Section 9.