Abstract:Based on the feature distance of generalized dimension, a speech endpoint detection method is proposed in order to detect the noisy-corrupted speech efficiently. Through calculating the generalized dimension by covering the signal with n-dimension boxes, three dimension feature vectors including the box dimension, the information dimension and the correlation dimension are got. Then dimension feature distance could be calculated and used to make a classification for the speech signal. Experimental results show that compared with the detection using one dimension feature only, the proposed method is more robust to the endpoint detection of speech signal containing different noise and SNR, especially for the lower SNR signal.
武薇; 范影乐; 庞全. 基于广义维数距离的语音端点检测方法[J]. 电子与信息学报, 2007, 29(2): 465-468 .
Wu Wei; Fan Ying-le; Pang Quan. A Speech Endpoint Detection Method Based on the Feature Distance of Generalized Dimension. , 2007, 29(2): 465-468 .