Accurate speech segmentation via the improved short-time fractal dimension
- Author:
Jinyan HU
1
Author Information
1. Sch. of Electronics and Info. Eng.
- Publication Type:Journal Article
- From:Academic Journal of Xi'an Jiaotong University
2003;15(2):139-142
- CountryChina
- Language:Chinese
-
Abstract:
Objective: To improve the accuracy of speech segmentation through the improved short-time fractal dimension. Methods: An equation was established for window size selection of speech analysis. Dynamic Window Step (DWS), a novel method to determine the sliding window steps adaptively in agreement with the local properties of signals, was proposed. Results: The influence of the window step on the short-time fractal dimension was discussed. Compared with fixed window steps, more accurate and efficient fractal dimension trajectories were obtained with dynamic window steps. Conclusion: The proposed method was applied to a number of speech signals. It shows promise in speech segmentation, speech recognition and other transient signal analysis.
