CAJ | 학술논문

提出了一种基于多级小波分解重构和非线性动力学参数的病理嗓音基音频率检测算法。首先对病理嗓音进行多级小波分解及重构，然后采用最大李雅普诺夫指数和近似熵表征不同重构嗓音的规则度从而自适应地选择周期性最优的小波重构嗓音信号，以直接提取基音频率。实验结果表明，与传统的基音检测算法相比，该方法有效地避免了检测中所存在的倍频及分频误差，提高了病理嗓音检测的鲁棒性及准确度。
제출료일충기우다급소파분해중구화비선성동역학삼수적병리상음기음빈솔검측산법。수선대병리상음진행다급소파분해급중구，연후채용최대리아보낙부지수화근사적표정불동중구상음적규칙도종이자괄응지선택주기성최우적소파중구상음신호，이직접제취기음빈솔。실험결과표명，여전통적기음검측산법상비，해방법유효지피면료검측중소존재적배빈급분빈오차，제고료병리상음검측적로봉성급준학도。
This paper proposes a new pitch detection algorithm of pathological voice based on discrete wave-let, largest lyapunov exponent and approximate entropy. Firstly, Daubechies'discrete wavelet transform is used to process the pathological voice, and then the most regular reconstructed signal is adaptively selected to detect period based on the two nonlinear dynamic parameters. Results show that this method could effec-tively avoid the detection of frequency doubling and frequency division error, and improve the robustness and accuracy of the pathologic voice detection.