基于分形维的语音去噪与音节分割

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 proposes an algorithm based on fractal theory. The algorithm first uses dynamic threshold algorithm which combines fractal dimension with wavelet transform to denoise the speech signal, it can extract pure speech as far as possible;on this basis,the paper designs the algorithm which is based on the mean of fractal dimension trajectory to carry out syllable segmentation. The experimental results show that the algorithms not only achieves speech denoising and syllable segmentation but also has good robustness.In the case of low SNR,the algorithm is still able to maintain high accuracy rate. It has better prospect in speech recognition field.%为提高现有小波去噪法的处理效果,准确有效判断出连续语音中各个音节的起止点,提出了基于分形理论的算法.该算法首先利用分形维与小波变换相结合的动态阈值算法进行语音去噪,从而提取出尽可能纯净的语音信号;在此基础上,计算分形维轨线,根据其均值对音节分割点进行判定.实验结果表明,该算法较好地实现了语音去噪和音节分割,鲁棒性较好,使得系统在低信噪比情况下仍保持较高准确率,在语音识别方面有较好应用前景.