Speech denoising and Syllable segmentation based on Fractal dimension

摘要：

In order to enhance the effect of existing wavelet denoising and determine beginning-ending points of each syllable in continuous speech, the thesis improves algorithms based on fractal theory. Firstly, the algorithm use dynamic threshold algorithm which combines fractal dimension with wavelet transform to denoise the speech signal; on this basis, the paper design an algorithm which is based on fractal dimension trajectory to carry out syllable segmentation. The experimental results show that the improved algorithms not only betterly carry out speech denoising and syllable segmentation, but also have good robustness. In the case of low SNR, the algorithm is still able to maintain high accuracy rate.

关键词： component speech recognition fractal dimension speech denoising syllable segmentation

作者: PAN Feng DING Na-na

作者单位: National Key Laboratory on ISN, Xidian University, Xian,China Network and Information Security Key Laboratory,Electronics Department, Engineering College of the A

会议类型: 国际会议

会议名称: 2010 International Conference on Measuring Technology and Mechatronics Automation(ICMTMA 2010)(2010年检测技术与机电自动化国际会议)

会议地点: 长沙

会议语种:英文

页码: 2687-2690

在线出版日期: 2010-03-13（万方平台首次上网日期，不代表论文的发表时间）