Detecting the Longest Periodic Timescale in Normal Vowels
Normal vowels are confirmed to have irregularities, where various methods have demonstrated that there is chaotic property hidden in them. However, little attention has been given to such phenomenon that, in short timescale, the vowel single usually shows periodic character and when the time length is long enough, it converts to chaotic dynamics. In this paper, we aim to search the longest time window that the normal vowel keeps its periodic dynamics. We employ a novel pseudoperiodic surrogate algorithm to test whether the normal vowel segment is consistent with the periodic orbit. The results reveal that the longest time window is invariant for different vowel data, and for most vowel data segment, they keep periodic dynamics given that their timescale is between 25ms and 35ms by investigating typical Chinese normal vowels from male and female subjects.
Huanhuan Zhang Yi Zhao Tongfeng Weng
Shenzhen Graduate School, Harbin Institute of Technology, Shenzhen, China
国际会议
上海
英文
1753-1757
2010-10-20（万方平台首次上网日期，不代表论文的发表时间）