CAJ | 학술논문

为了进行有效的语音信号处理,降低语音信号的冗余度,通常采用端点检测技术来提取语音信号中的有效部分.而传统谱熵端点检测算法由于判定门限为固定值,其在低信噪比条件下检测性能急剧下降,提出了一种基于动态加权门限的检测方法,对每个判定的噪音帧的谱熵与无声段噪音谱熵进行加权平均,得到新的噪音谱熵作为更新后的门限值;在判定过程中引入谱减法提高信噪比,进一步降低噪声干扰.仿真实验结果证明,相对于传统谱熵端点检测方法,该方法在低信噪比的条件下仍然能够更为准确地检测到语音的端点.
위료진행유효적어음신호처리,강저어음신호적용여도,통상채용단점검측기술래제취어음신호중적유효부분.이전통보적단점검측산법유우판정문한위고정치,기재저신조비조건하검측성능급극하강,제출료일충기우동태가권문한적검측방법,대매개판정적조음정적보적여무성단조음보적진행가권평균,득도신적조음보적작위경신후적문한치;재판정과정중인입보감법제고신조비,진일보강저조성간우.방진실험결과증명,상대우전통보적단점검측방법,해방법재저신조비적조건하잉연능구경위준학지검측도어음적단점.
In order to increase the speech signal’s efficiency and decrease the redundancy of the speech signal, the valid infor-mation of speech signal is often extracted by endpoint detection technology. However, the accuracy of traditional spectral entro-py endpoint detection is decreased rapidly in low Signal-to-Noise condition. This paper proposes a method which is based on weighing threshold. Every spectral entropy of noise frame will be weighed with the initial noisy spectral entropy. The new weighed spectral entropy will be used as the refreshed threshold. At the same time, the spectral subtraction is used in the deci-sion procedure to boost up the SNR and keep the robustness. The experiment results indicate that the accuracy of the speech end-point detection has been improved in low SNR condition.