کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
4977778 | 1452008 | 2017 | 18 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Automatic syllable segmentation algorithm of Chinese speech based on MF-DFA
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موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
پردازش سیگنال
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چکیده انگلیسی
Automatic speech segmentation algorithm plays an important role in speech recognition and spoken term detection. A method called automatic syllable segmentation of Chinese speech based on multi-fractal detrended fluctuation analysis (MF-DFA) is explored in this study. The algorithm attempts to improve the precision and robustness of Chinese syllable segmentation. Firstly, the multi-fractal characteristics of Chinese syllables based on MF-DFA are explored. Secondly, to solve the problem with the unclear boundary of adjacent finals, which leads to the unsatisfactory precision rate of Chinese syllable segmentation in existing algorithms, two-stage voiced decision algorithm is introduced. Finally, the generation of dividing point works by detecting the extreme points of the first-order differential curve for each voiced segment. The experimental results indicated that the multi fractal characteristics based on MF-DFA possess good distinction and robustness, and the proposed algorithm outperforms the earlier approaches in terms of the performance of Chinese syllable segmentation even in low SNR.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Speech Communication - Volume 92, September 2017, Pages 42-51
Journal: Speech Communication - Volume 92, September 2017, Pages 42-51
نویسندگان
He Shaofang, Zhao Huan,