中文摘要：

基于整体，实验模式分解(EEMD ) 为精确地检测用音调的语言改变讲话的沥青的时间被建议的一个方法。不同框架 -- ，事件 -- ，或基于 subspace 的沥青察觉者，在短持续时间以内改变沥青的信息的时间，具有在音调的语言的语音处理的关键重要性，能精确地被提取。为国语的中国语言学数据协会(CLDC ) 数据库为方法的有效性的评估作为标准讲话数据被采用。建议方法提供更精确、可靠的结果，这被显示出，特别地在估计 non-monotonically 改变象用国语的第三一样的程度的音调。另外，新方法有强壮的抵抗到噪音骚乱，这被显示出。

英文摘要：

A method based on ensemble empirical mode decomposition （EEMD） is proposed for accurately detecting the time varying pitch of speech in tonal languages. Unlike frame-, event-, or subspace-based pitch detectors, the time varying information of pitch within the short duration, which is of crucial importance in speech processing of tonal languages, can be accurately extracted. The Chinese Linguistic Data Consortium （CLDC） database for Mandarin Chinese was employed as standard speech data for the evaluation of the effectiveness of the method. It is shown that the proposed method provides more accurate and reliable results, particularly in estimating the tones of non-monotonically varying pitches like the third one in Mandarin Chinese. Also, it is shown that the new method has strong resistance to noise disturbance.